Trusted Autonomy


School of Engineering and Information Technology
University of New South Wales - Canberra - Australia


Home


Publications


2015

  1. Abbass H.A. (2015) Computational Red Teaming: Risk Analytics of Big-Data-to-Decisions Intelligent Systems, Springer International Publishing Switzerland. ISBN 978-3-319-08280-6(Hard Cover), 978-3-319-08281-3 (EBook), ISBN-10 3319082809, doi:10.1007/978-3-319-08281-3.
  2. P.Li, M.Garratt, A.Lambert, (2015) Monocular Snapshot-based Sensing and Control of Hover, Takeoff, and landing for a Low-cost Quadrotor,¯ Journal of Field Robotics.
  3. Wang J; Garratt M; Anavatti S, (2015), 'Dominant plane detection using a RGB-D camera for autonomous navigation', in ICARA 2015 - Proceedings of the 2015 6th International Conference on Automation, Robotics and Applications, Institute of Electrical and Electronics Engineers Inc., pp. 456 “ 460.
  4. P.Li, M.Garratt, A.Lambert, (2015) Sensing and control of a quadrotor using a visual inertial fusion method,¯ 15th International Conference on Control, Automation and Systems (ICCAS 2015), (to appear).
  5. P.Li, M.Garratt, A.Lambert, (2015) A homography-based visual inertial fusion method for robust sensing of a Micro Aerial Vehicle,¯ 2015 IEEE International Conference on Mechatronics and Automation, Beijing, China (to appear).
  6. S.Lin, M.Garratt, A.Lambert (2015) Real-Time 6DoF Deck Pose Estimation and Target Tracking for Landing an UAV in a Cluttered Shipboard Environment using On-board Vision,¯ 2015 IEEE International Conference on Mechatronics and Automation, Beijing, China (to appear).
  7. Harvey, J., Merrick, K., Abbass, H.: (2015) Application of chaos measures to a simplified boids flocking model, Swarm Intelligence, 9(1):23-41.
  8. Maher, M-L., Merrick, K., Wang, B., (2015) Reasoning and Making Sense of Data in the Absence of Goals, Advances in Cognitive Systems Workshop on Goal Reasoning, May 28-31, Atlanta, Georgia.
  9. Swiechowski, M., Merrick, K., Mandziuk, J., Abbass, H.: (2015) Human-Machine Cooperation in General Game Playing, Eighth International Conference on Advances in Computer-Human Interactions, Lisbon, Portugal, pp 96-100.
  10. Wang, B., Merrick, K., Abbass, H.: (2015) Autonomous Hypothesis Generation as an Environment Learning Mechanism for Agent Design, Australian Conference on Artificial Life and Computational Intelligence, Lecture Notes in Computer Science Volume 8955, 2015, pp 210-225
  11. Goh, S. K., Abbass, H. A., Tan, K. C., & Al Mamun, A. (2015). Evolutionary Big Optimization (BigOpt) of Signals. IEEE CEC, Japan.
  12. Al-Ani, A., Naik, G. R., & Abbass, H. A. (2015, November). A Methodology for Synthesizing Interdependent Multichannel EEG Data with a Comparison Among Three Blind Source Separation Techniques. In Neural Information Processing (pp. 154-161). Springer International Publishing.
  13. Derevyanko, N., Anavatti S.G. and Ray T.(2015) Intelligent Underwater Vehicle with Multi-role capabilities, Proceedings of the 6th International Conference on Automation, Robotics and Applications, ICARA, New Zealand.
  14. Halder K.K., Tahtali M. and Anavatti S.G., (2015). Turbulence Mitigation and Moving Object Detection for Underwater Imaging. International Conference on Optical Instuments and Technology; Optoelectronic Imaging and Processing Technology, Proceeding SPIE Vol. 9622.
  15. Halder, K. K., Tahtali, M., and Anavatti, S. G. (2015). Geometric correction of atmospheric turbulence-degraded video containing moving objects. Optics Express, 23(4).
  16. Kirsanov A, Anavatti S.G. and Ray T., (2015) Hybrid path-planning algorithm in two-dimensional and three-dimensional spaces. Proceedings of the 6th International Conference on Automation, Robotics and Applications, ICARA, New Zealand.
  17. Kirsanov A, Anavatti S.G. and Ray T., (2015. Smart vehicle design for underwater applications with low-acoustic noise. Proceedings of the 6th International Conference on Automation, Robotics and Applications, ICARA, New Zealand.
  18. Pratama, M., Anavatti, S. G., Joo, M., and Lughofer, E. D. (2015). pClass: An Effective Classifier for Streaming Examples. IEEE Transactions on Fuzzy Systems, 23(2).
  19. Pratama, M., Lu, J, Anavatti S.G. and Lughofer, E., (2015). An incremental meta-cognitive-based scaffolding fuzzy neural network. Neurocomputing (In press, online available).
  20. N. Hamza, D. Essam and R. Sarker (2015) Constraint Consensus Mutation based Differential Evolution for constrained optimization, IEEE Transactions on Evolutionary Computation, Conditionally Accepted (Impact Factor: 3.654; 2010 ERA A*)
  21. M. F. Zaman, S. Elsayed, T. Ray and R. Sarker (2015) Evolutionary Algorithms for Dynamic Economic Dispatch Problems, IEEE Transactions on Power Systems, Accepted (29/4/15) (ISI Impact Factor: 2.814; 2010 ERA A*)
  22. M. H. F. Rahman, R. Sarker and D. Essam (2015) A Real-Time Order Acceptance and Scheduling Approach for Permutation Flow Shop Problems, European Journal of Operational Research, Accepted (Impact Factor: 2.358; 2010 ERA A)
  23. R. Sarker, D. Essam, S M K Hasan and A N M Karim (2015) Managing Risk in Production Scheduling under Uncertain Disruption, Artificial Intelligence for Engineering Design, Analysis and Manufacturing, Accepted (7/4/15), (2013 ISI Impact Factor: 0.604; 2010 ERA A).
  24. P. C. Jha, S. Aggarwal, A. Gupta and R. Sarker (2015) Multi-criteria Media Mix Decision Model for Advertising a Single Product with Segment Specific and Mass Media. Journal of Industrial and Management Optimization, Accepted. (Impact Factor: 0.834)
  25. M. Omar and R. Sarker (2015) An Optimal Policy for a Just-in-Time Integrated Manufacturing System for Time-Varying Demand Process, Applied Mathematical Modelling, Accepted (ISI Impact Factor: 2.251)
  26. Shah Z, Mahmood AN, Barlow M (2015) Computing discounted multidimensional hierarchical aggregates using modified Misra Gries algorithm, Performance Evaluation, July 2015.
  27. S. K. Paul, R. Sarker and D. Essam (2015) Managing Risk and Disruption in Production-Inventory and Supply Chain Systems: A Review, Journal of Industrial and Management Optimization, Accepted (Impact Factor: 0.843)
  28. R. Sarker and S. Elsayed (2015) Evolutionary Algorithm for Analyzing Higher Degree Research Student Recruitment and Completion, Cogent Engineering, An Open Access Journal by Taylor & Francis, http://dx.doi.org/10.1080/23311916.2015.1063760.
  29. Paul, S. K., Sarker, R., and Essam, D. (2015) A disruption recovery plan in a three-stage production-inventory system, Computers & Operations Research, 57, pp.60-72 (Impact Factor: 1.861; 2010 ERA A)
  30. Asafuddoula, M., Ray, T., and Sarker, R. (2015) Improved self-adaptive constraint sequencing approach for constrained optimization problems, Applied Mathematics and Computation, 253, pp. 23-39 (Impact Factor: 1.551; 2010 ERA A)
  31. Asafuddoula, M., Ray, T., and Sarker, R. (2015) A Decomposition Based Evolutionary Algorithm for Many Objective Optimization, IEEE Transactions on Evolutionary Computation, 19 (3), 6857344, pp. 445-460 (Impact Factor: 3.654; 2010 ERA A*).
  32. Sayed, E., Essam, D., Sarker, R. and Elsayed, S. (2015) Decomposition-based evolutionary algorithm for large scale constrained problems, Information Sciences, 316, pp. 457-486. (Impact Factor: 4.038)
  33. Abdesselam, M., Karim, A. N. M., Emrul Kays, H. M., Rahman, M. A. and Sarker, R. (2015) Formulation of an IP-based model for reactive flow-shop scheduling problem subject to arrival of new orders, Advanced Materials Research, ISSN 1022-6680, 1115, pp.616-621 (ERA B)
  34. Elsayed, S., Sarker, R., and Essam, D. (2015) Training and Testing a Self-Adaptive Multi-Operator Evolutionary Algorithm for Constrained Optimization, Applied Soft Computing, 26, pp.515-522 (Impact Factor: 2.810)
  35. Sallam, K., Sarker, R., Essam, D. and Elsayed, S. (2015) Neurodynamic Evolutionary Algorithm and Solving CEC2015 Competition Problems, 2015 IEEE Congress on Evolutionary Computation, 25-28th May, Sendai, Japan, Accepted 26/02/2015
  36. Elsayed, S., Sarker, R. and Slay, J. (2015) Evaluating the Performance of A Differential Evolution Algorithm in Anomaly Detection, 2015 IEEE Congress on Evolutionary Computation, 25-28th May, Sendai, Japan, Accepted 26/02/2015
  37. Elsayed, S. and Sarker, R. (2015) Adaptive Configuration of Differential Evolution Algorithms for Big Data, 2015 IEEE Congress on Evolutionary Computation, 25-28th May, Sendai, Japan, Accepted 26/02/2015
  38. Ali, I., Elsayed, S., Ray, T. and Sarker, R. (2015) Memetic Algorithm for solving Resource Constrained Project Scheduling Problems, 2015 IEEE Congress on Evolutionary Computation, 25-28th May, Sendai, Japan, Accepted 26/02/2015

2014

  1. Wang J; Garratt M; Li P; Anavatti S, (2014), 'Motion recovery using the image interpolation algorithm and an RGB-D camera', in 2014 IEEE International Conference on Robotics and Biomimetics, IEEE ROBIO 2014, Institute of Electrical and Electronics Engineers Inc., pp. 683 “ 688.
  2. Merrick, K.: (2014) Evolution of Intrinsic Motives in a Multi-Player Common Pool Resource Game, IEEE Symposium Series on Computational Intelligence, pp 36-43. [Nominated for best paper award]
  3. Ismail, H., Merrick, K., Barlow, M.: (2014) Self-Motivated Learning of Achievement and Maintenance Tasks for Non-Player Characters in Computer Games, IEEE Symposium Series on Computational Intelligence, pp 44-51.
  4. Hardhienata, M., Merrick, K., Ugrinovskii, V.: (2014) Effective Motive Profiles and Swarm Compositions for Motivated Particle Swarm Optimisation Applied to Task Allocation, IEEE Symposium Series on Computational Intelligence pp 52-59.
  5. Hardhienata, M., Ugrinovskii, V., Merrick, K.: (2014) Task allocation under communication constraints using motivated particle swarm optimisation, IEEE Congress on Evolutionary Computation pp 3135-3142.
  6. Debie, E., Shafi, K., Merrick, K., Lokan, C.: (2014) An online evolutionary rule learning algorithm with incremental attribute discretisation, IEEE Congress on Evolutionary Computation pp 1116-1123.
  7. Liu J., Green D.G., Abbass H.A. (2014) Dual Phase Evolution: from Theory to Practice, Springer, ISBN-10 1441984224.
  8. Abbass H.A., Jiangjun T., Ellejmi M., Kirby S. (2014) Visual and auditory reaction time for air traffic controllers using quantitative electroencephalograph (QEEG) data, Brain Informatics, no. 2198-4018.
  9. Leu G., Curtis N., and Abbass H.A. (2014) Society of Mind cognitive agent architecture applied to drivers adapting in a traffic context, Adaptive Behaviour, vol. 22, no. 2, pp. 123 - 145.
  10. Abbass H.A., Tang J., Amin R., Ellejmi M., Kirby S. (2014) The computational air traffic control brain: Computational red teaming and big data for real-time seamless brain-traffic integration, Journal of Air Traffic Control, vol. 52, no. 2, pp. 10 “ 17.
  11. Xiong J., Liu J., Chen Y., and Abbass H.A. (2014) A Knowledge-based Evolutionary Multi-objective Approach for Stochastic Extended Resource Investment Project Scheduling Problems. IEEE Transactions on Evolutionary Computation, vol. 18, no. 5, pp. 742 - 763.
  12. Zhao W., Alam S., Abbass H.A. (2014) MOCCA-II: A multi-objective co-operative co-evolutionary algorithm', Applied Soft Computing, vol. 23, pp. 407 “ 416.
  13. Nguyen L., Bui L. and Abbass H.A. (2014) DMEA-II: the Direction-based Multi-objective Evolutionary Algorithm - II, Soft Computing, vol. 18, no. 11, pp. 2119 - 2134.
  14. Petraki E. and Abbass H.A. (2014) On Trust and Influence: A Computational Red Teaming Game Theoretic Perspective. IEEE Computational Intelligence in Defence and Security Symposium, Hanoi, December 2014.
  15. Rafael Falcon, Rami Abielmona, Sean Billings, Alex Plachkov and Hussein Abbass (2014) Risk Management with Hard-Soft Data Fusion in Maritime Domain Awareness. IEEE Computational Intelligence in Defence and Security Symposium, Hanoi, December 2014.
  16. Abbass, H. A. (2014). Calibrating independent component analysis with laplacian reference for real-time EEG artifact removal. LNCS 8836, Springer, 68-75.
  17. Goh, S. K., Abbass, H. A., Tan, K. C., & Al Mamun, A. (2014). Artifact Removal from EEG Using a Multi-objective Independent Component Analysis Model. LNCS 8834, Springer, 570-577.
  18. Leu G., Tang J., and Abbass H.A. (2014) On the role of working memory in trading-off skills and situation awareness in Sudoku, LNCS 8836, Springer, 571-578.
  19. Ren, S., Tang, J., Barlow, M., & Abbass, H. A. (2014, July). An interactive evolutionary computation framework controlled via EEG signals. In Fuzzy Systems (FUZZ-IEEE), 2014 IEEE International Conference on (pp. 2402-2409). IEEE.
  20. Tang J. & Abbass H.A. (2014) Learning the Behavior of Aircraft Landing Sequencing using a Society of Probabilistic Finite State Machines, IEEE WCCI, Beijing, China, pp. 610-617.
  21. Amin R., Tang J., Ellejmiy M., Kirbyy S., and Abbass H.A. (2014) Trading-off Simulation Fidelity and Optimization Accuracy in Air-Traffic Experiments using Differential Evolution, IEEE WCCI, Beijing, China, pp. 475-482.
  22. Zhang B., Shafi K., and Abbass H.A. (2014) Online Knowledge-based Evolutionary Multi-Objective Optimization, pp. IEEE WCCI, Beijing, China, pp. 2222-2229.
  23. Pratama, M., Anavatti, S. G., and Lughofer, E. (2014). GENEFIS: Toward an Effective Localist Network. IEEE Transactions on Fuzzy Systems, 22(3).
  24. Li, C., Anavatti, S. G., and Ray, T. (2014). Analytical Hierarchy Process Using Fuzzy Inference Technique for Real-Time Route Guidance System. IEEE Transactions on Intelligent Transportation Systems, 15(1).
  25. Pratama, M., Anavatti, S. G., Angelov, P. P., and Lughofer, E. (2014). PANFIS: A Novel Incremental Learning Machine. IEEE Transactions on Neural Networks and Learning Systems, 25(1).
  26. Pratama, M., Lu, J, Anavatti S.G. and Iglesias, J.A. (2014). A recurrent meta-cognitive-based Scaffolding classifier from data streams. Proceedings of Evolving and Autonomous Learning Systems (EALS), Orlando, FL, USA
  27. Tahtali, M., Anavatti, S. G., and Halder, K. K. (2014). Simple algorithm for correction of geometrically warped underwater images. Electronics Letters, 50(23).
  28. Halder, K. K., Tahtali, M., and Anavatti, S. G. (2014). Model-free prediction of atmospheric warp based on artificial neural network. Applied Optics, 53(30).
  29. Halder, K. K., Tahtali, M., and Anavatti, S. G. (2014). High accuracy image restoration method for seeing through water. Applications of Digital Image Processing XXXVII Vol. 9217 San Diego, United States.
  30. Halder, K. K., Tahtali, M., and Anavatti, S. G. (2014). Simple and efficient approach for restoration of non-uniformly warped images. Applied Optics, 53(25).
  31. Alam, K., Ray, T., and Anavatti, S.G.(2014). Practical Application of an Evolutionary Algorithm for the Design and Construction of a Six-inch Submarine. In D. Liu (Ed.), Proceedings of the 2014 IEEE Congress on Evolutionary Computation (CEC 2014) (pp. 2825-2832). Beijing, China.
  32. Pratama, M., Meng Joo Er., Anavatti.S.G and Edwin Lughofer., (2014). A Novel Meta-Cognitive-based Scaffolding Classifier to Sequential Non-stationary Classification Problems. In L. Derong (Ed.), Proceedings of IEEE WCCI 2014 (pp. 369-376). Beijing,China.
  33. Pratama, M., Anavatti, S.G., and Lughofer, E. (2014). An Incremental Classification from Data Streams with Parsimonious Classifier. Lecture Notes in Computer Science, Artificial Intelligence: Methods and Applications: Vol. 8445 (pp. 15-28), Springer.
  34. Alam, K., Ray, T., and Anavatti, S. G. (2014). A brief taxonomy of autonomous underwater vehicle design literature. Ocean Engineering, 88.
  35. Halder, K. K., Tahtali, M., and Anavatti, S. G. (2014). A new image restoration approach for imaging through the atmosphere. In 2013 IEEE International Symposium on Signal Processing and Information Technology(ISSPIT) (pp. 000350-000355). Athens, Greece.
  36. Halder, K. K., Tahtali, M., and Anavatti, S. G. (2014). A New Pixel Shiftmap Prediction Method Based on Generalized Regression Neural Network. In 2013 IEEE International Symposium on Signal Processing and Information Technology(ISSPIT), (pp. 000309-000314). Athens, Greece.
  37. Halder, K. K., Tahtali, M., and Anavatti, S. G. (2014). An Artificial Neural Network Approach for Underwater Warp Prediction. Lecture Notes in Computer Science, Artificial Intelligence: Methods and Applications, 8445, 384-394, Springer.
  38. Alam, K., Ray, T., and Anavatti, S. G. (2014). Design and construction of an autonomous underwater vehicle. Neurocomputing, 142.
  39. Halder, K. K., Tahtali, M., and Anavatti, S. G. (2014). Restoration of Non-Uniformly Warped Noisy Images Based on Coarse-to-Fine Optical Flow Estimation. In 2013 16th International Conference on Computer and Information Technology (ICCIT), Khulna, Bangladesh.
  40. Sarker, R., Elsayed, S. and Ray, T. (2014) Differential Evolution with Dynamic Parameters Selection for Optimization Problems, IEEE Transactions on Evolutionary Computation, 18(5), pp689-707. (Impact Factor: 3.654; 2010 ERA A*).
  41. Paul, S. K., Sarker, R., and Essam, D. (2014) Disruption Management for a Two-Stage Production-Inventory System with Reliability Considerations, European Journal of Operational Research, 237, pp113-128 (Impact Factor: 2.358; 2010 ERA A)
  42. Hamza, N., Sarker, R., Essam, D., Deb. K., and Elsayed, S. (2014) A Constraint Consensus Memetic Algorithm for Solving Constrained Optimization Problems, Engineering Optimization, 46(11), pp1447-1464 (Impact Factor: 1.076; 2010 ERA A)
  43. Elsayed, S., Sarker, R., and Essam, D. (2014) A Self-Adaptive Combined Strategies Algorithm for Constrained Optimization using Differential Evolution, Applied Mathematics and Computation, 241, pp267-282 (Impact Factor: 1.551; 2010 ERA A)
  44. Asafuddoula, M., Ray, T., and Sarker, R. (2014) An Adaptive Hybrid Differential Evolution Algorithm for Single Objective Optimization, Applied Mathematics and Computation, 231, pp.601-618 (Impact Factor: 1.551; 2010 ERA A).
  45. Elsayed, S., Sarker, R., and Mezura-Montes, E. (2014) Self-Adaptive Mix of Particle Swarm Methodologies for Constrained Optimization, Information Sciences, 227, ppp216-233 (ISI Impact Factor: 4.038).
  46. Elsayed, S., Sarker, R., and Essam, D. (2014) A New Genetic Algorithm for Solving Optimization Problems, Engineering Applications of Artificial Intelligence, 27, pp.57-69 (Impact Factor: 2.207)
  47. Li, P., Guo, S., Hu, J. and Sarker, R. (2014) Lifetime Optimization for Reliable Broadcast and Multicast in Wireless Ad-hoc Networks, Wireless Communications and Mobile Computing, 14(2), 221-231 (Impact Factor: 0.858, 2010 ERA A)
  48. Paul, S. K., Sarker, R., and Essam, D. (2014) Managing Real-time Demand Fluctuation under a Supplier-Retailer Coordinated System, International Journal of Production Economics, 158, pp231-243 (Impact Factor: 2.752; 2010 ERA A)
  49. H. Hishamuddin, R. Sarker and D Essam (2014) A Recovery Mechanism for a Two Echelon Supply Chain System under Supply Disruption, Economic Modelling, 38, pp555-563, (Impact Factor: 0.872; 2010 ERA A)
  50. Paul, S. K., Sarker, R., and Essam, D. (2014) Managing Disruption in an Imperfect Production-Inventory System, Computers & Industrial Engineering, In Press, Accepted 9/2014, DOI:10.1016/j.cie.2014.09.013 (Impact Factor: 1.783).
  51. Abdesselam, M., Karim, A. N. M., Emrul Kays, H. M., and Sarker, R. (2014) Forecasting demand: Development of a fuzzy growth adjusted holt-winters approach, Advanced Materials Research, ISSN 1022-6680, 903, pp.402-407. (ERA B)
  52. Paul, S. K., Azeem, A., Sarker, R., and Essam, D. (2014) Development of a Production Inventory Model with Uncertainty and Reliability Considerations, Optimization and Engineering, 15, pp.697-720 (Impact Factor: 1.233).
  53. Hermadi, I., Lokan, C. and Sarker, R. (2014) Dynamic Stopping Criteria for Search-based Test Data Generation for Path Testing, Information and Software Technology, 56(4), 395-407. (Impact Factor: 1.046).
  54. Abdallah, A., Essam, D. and Sarker, R. (2014) Solving dynamic optimisation problem with variable dimensions (DOPVD), Lecture Notes in Computer Science (LNCS), 10th International Conference on Simulated Evolution And Learning (SEAL2014), Dunedin, New Zealand, vol.-8886, pp.1-12.
  55. Chakrabortty, R. K., Sarker, R. and Essam, D. (2014) Event Based Approaches for Solving Multi-mode Resource Constraints Project Scheduling Problem, Lecture Notes in Computer Science (LNCS), 13th International Conference on Computer Information Systems and Industrial Management Applications (CISIM™2014), Ho Chi Minh City, Vietnam, Vol.-8838, pp.375-388.
  56. Greenwood, G., Elsayed, S., Sarker, R. and Abbass, H. (2014) Online Generation of Trajectories for Autonomous Vehicles Using a Multi-Agent System, 2014 IEEE Congress on Evolutionary Computation, July 6-11, Beijing, China, pp1218-1224
  57. Elsayed, S. and Sarker, R. (2015) Evolving the Parameters of Differential Evolution using Evolutionary Algorithms, The 18th Asia Pacific Symposium on Intelligent and Evolutionary Systems (IES™2014), 10-12th November 2014, Singapore, Proceedings in Adaptation, Learning and Optimization, Springer, Volume 1, pp 523-534.
  58. Elsayed, S., Sarker, R., Essam, D., and N. Hamza (2014) Testing United Multi-Operator Evolutionary Algorithms on the CEC2014 Real-Parameter Numerical Optimization, 2014 IEEE Congress on Evolutionary Computation, July 6-11, Beijing, China, pp1650-1657 (ERA Conference Ranking: A) (Received Best Algorithm Award for Real-Parameter Single Objective Optimization Competition)
  59. Hamza, N., Sarker, R., and Essam, D. (2014) Differential Evolution with a Constraint Consensus Mutation for Solving Optimization Problems, 2014 IEEE Congress on Evolutionary Computation, July 6-11, Beijing, China, pp991-997
  60. Elsayed, S., Sarker, R., and Essam, D. (2014) United Multi-Operator Evolutionary Algorithms, 2014 IEEE Congress on Evolutionary Computation, July 6-11, Beijing, China, pp1006-1013 (ERA Conference Ranking: A)
  61. Rahman, H. F., Sarker, R., Essam, D. and Chang, G. (2014) A Memetic Algorithm for Solving Permutation Flow Shop Problems with Known and Unknown Machine Breakdowns, 2014 IEEE Congress on Evolutionary Computation, July 6-11, Beijing, China, pp42-49
  62. Elsayed, S., Ray, T. and Sarker, R. (2014) A Surrogate-Assisted Differential Evolution Algorithm with Dynamic Parameters Selection for Solving Expensive Optimization Problems, 2014 IEEE Congress on Evolutionary Computation, July 6-11, Beijing, China, pp1062-1068
  63. Sayed, E., Sarker, R., Essam, D. and Elsayed, S. (2014) A Decomposition-Based Algorithm for Dynamic Economic Dispatch Problems, 2014 IEEE Congress on Evolutionary Computation, July 6-11, Beijing, China, pp1898-1907
  64. Paul, S. K., Sarker, R., and Essam, D. (2014) Managing Supply Disruption in a Three-Tier Supply Chain with Multiple Suppliers and Retailers, 2014 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM™2014), 9-12 December, Kuala Lumpur, Malaysia.
  65. Zaman, M. F., Sarker, R., and Ray, T. (2014) Solving an Economic and Environmental Dispatch Problem using Evolutionary Algorithm, 2014 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM™2014), 9-12 December, Kuala Lumpur, Malaysia.
  66. Piyadigamage S, Barlow MG, Easton A (2014) An Evaluation of DTW Approaches for Whole-of-Body Gesture Recognition, HCI 2014, Southport, UK, 09 Sep 2014 - 12 Sep 2014. Proceedings editors: Lumsden J, Rouncefield M. Proceedings of HCI 2014. 09 Sep 2014
  67. Ren S, Tang J, Barlow M, Abbass HA (2014) An interactive evolutionary computation framework controlled via EEG signals, 2014 IEEE International Conference on Fuzzy Systems, 06 Jul 2014 - 11 Apr 2015. IEEE International Conference on Fuzzy Systems. Institute of Electrical and Electronics Engineers Inc.. 2402-2409. 04 Sep 2014
  68. Baldwin T, Barlow MG (2014) Immersion & Engagement: The Relationship Of Interaction Fidelity To User Immersion, SimTecT, Adelaide, 25 Aug 2014 - 28 Aug 2014. Proceedings editors: Crea T. Proceedings of SimTecT 2014. 25 Aug 2014

2013

  1. S.Francis, S.Anavatti and M.Garratt, (2013) Model Based Path Planning module,¯ Recent Advances in Robotics and Automation, Studies in Computational Intelligence 480, Springer-Verlag, Berlin Heidelberg, pp 81“90.
  2. M.Garratt, A.Lambert and H.Teimoori, (2013) Design of a 3D Snapshot based Visual Flight Control System using a Single Camera in Hover,¯ Autonomous Robots, vol. 34, no. 1“2, pp. 19“34, 2013.
  3. M.C.Hoy, M.Garratt, Decentralized DeadlockFree Navigation for Multiple Vehicles in 2D and 3D Environments using Local Parametized Trajectory Generation, (2013)¯ In Australian Conference on Robotics and Automation 2013, Sydney, Australia, 2“4 Dec 2013.
  4. S.Francis, S.Anavatti and M.Garratt, (2013) Real time Cooperative Path planning for Multi-Autonomous Vehicles,¯ In 2nd International Conference on Advances in Computing, Communications and Informatics (ICACCI 2013), Mysore, India, 22“25 Aug 2013.
  5. G.Sun, Y.Li, J.Xie, M.Garratt and C.Wang, (2013) Implementing quaternion based AHRS on a MEMS multisensor hardware platform,¯ In IGNSS Symposium, Gold Coast, Australia, 16“18 July 2013.
  6. P.Li, M.Garratt, A.Lambert, M.Pickering, J.Mitchell, (2013) Onboard Hover Control of a Quadrotor using Template Matching and Optic Flow,¯ In The 2013 International Conference on Image Processing, Computer Vision and Pattern Recognition, Las Vegas, USA, 22“25 Jul 2013.
  7. M.Garratt, L.Scott, A.Lambert, P.Li, (2013) Flight Test Results of a 2D Snapshot Hover,¯ In 2013 IFAC Intelligent Autonomous Vehicles Symposium, Gold Coast, Australia, 26“28 Jun 2013.
  8. X.Yang, L.M.Alvarez, M.Garratt and H.R. Pota, (2013) A Flight Control Scheme to Improve Position Tracking Performance of Rotary-Wing UASs,¯ In 2013 IFAC Intelligent Autonomous Vehicles Symposium, Gold Coast, Australia, 26“28 Jun 2013.
  9. M.Pratama, S.Anavatti, M.Garratt and E.Lughofer, (2013) Online Identification of Complex Multi“Input“Multi“Output System Based on Generic Evolving Neuro“Fuzzy Inference System,¯ In 2013 IEEE Conference on Evolving and Adaptive Intelligent Systems (EAIS), Singapore, 16“19 Apr 2013.
  10. M.Pratama, S.Anavatti and M.Garratt, (2013) Online Identification of Complex Multi-Input-Multi-Output System Based on GENEFIS,¯ In IEEE Symposium Series on Computational Intelligence (SSCI2013), Singapore, 15“18 Apr 2013.
  11. Merrick, K.: (2013) Novelty and beyond: towards combined motivation models and integrated learning architectures, in Baldassarre G., Mirolli, M., (Eds) Intrinsically Motivated Learning in Natural and Artificial Systems, pp 235-259. ISBN: 978-3-642-32374-4. [Invited book chapter].
  12. Merrick, K., Shafi, K.: (2013) A Game Theoretic Framework for Incentive-Based Models of Intrinsic Motivation in Artificial Systems ,Frontiers in Cognitive Science, Special Issue on Intrinsic Motivations and Open-Ended Development in Animals, Humans and Robots.Baldassarre, G., Barto, A., Mirolli, M., Redgrave, P., Ryan, R., Stafford, T (Eds). Volume 4, 30th October, 2013.
  13. Debie, E., Shafi, K., Lokan, C., Merrick, K.: (2013) Performance Analysis of Rough Set Ensemble of Learning Classifier Systems with Differential Evolution based Rule Discovery, Evolutionary Intelligence, 6(2):109-126.
  14. Merrick, K., Isaacs, A., Barlow, M., Gu, N.: (2013) A Shape Grammar Approach to Computational Creativity and Procedural Content Generation in Massively Multiplayer Online Role-Playing Games, Entertainment Computing, Elsevier, Rauterberg, M. (Ed.), 4(2):15-130.
  15. Debie, E., Shafi, K., Lokan, C., Merrick, K.: (2013) Investigating Differential Evolution Based Rule Discovery in Learning Classifier Systems, IEEE Symposium Series on Computational Intelligence, pp 77-84.
  16. Debie, E., Shafi, K., Lokan, C., Merrick, K.: (2013) Reduct Based Ensemble of Learning Classifier System for Real-Valued Classification Problems, IEEE Symposium Series on Computational Intelligence, pp 66-73.
  17. Tian, B., Merrick, K., Yu, S., Hu, J.: (2013) A Hierarchical PCA-based Anomaly Detection Model, 2013 International Conference on Computing, Networking and Communications, Communications and Information Security Symposium, pp 621-625
  18. Alam S., Lokan C., Aldis G., Barry S., Butcher R., and Abbass H.A. (2013) Systemic Identification of Airspace Collision Risk Tipping points using an Evolutionary Multi-Objective Scenario-based Methodology, Transportation Research Part C, Elsevier, vol. 35, pp. 57 - 84.
  19. Shafi K. and Abbass H.A. (2013) Evaluation of an Adaptive Genetic-Based Signature Extraction System for Network Intrusion Detection, Pattern Analysis and Applications, Springer, vol. 16, no. 4, pp. 549 - 566.
  20. Zhao W., Alam S. and Abbass H.A. (2013) Evaluating Ground-Air Network Vulnerability in an Integrated Terminal Maneuvering Area Using Co-evolutionary Computational Red Teaming, Transportation Research Part C, Elsevier, 29(4), 32-54.
  21. Wang S., Shafi K., Lokan C., and Abbass H.A. (2013) An agent based model to simulate and analyse behaviour under noisy and deceptive information, Adaptive Behaviour, Sage, 21(2), 96-117, 2013.
  22. Rubai A., Tang J., Ellejmi M., Kirby S., and Abbass H.A. (2013) Computational Red Teaming for Correction of Traffic Events in Real Time Human Performance Studies, USA/Europe ATM R&D Seminar, Chicago, IL, USA,2013
  23. Nguyen L., Bui L. and Abbass H.A (2013) A New Niching Method for the Direction-based Multi-objective Evolutionary Algorithm, IEEE Symposium Series on Computational Intelligence, Singapore.
  24. Alam S., Hossain M., Lokan C., Barry S., Aldis G., Butcher R. and Abbass H.A. (2013) Real Time Prediction of Worst Case Air Traffic Sector Collision Risk using Evolutionary Optimization, IEEE Symposium Series on Computational Intelligence, Singapore.
  25. Amin R., Tang J., Ellejmi M., Kirby S. and Abbass H.A. (2013) An Evolutionary Goal-Programming Approach Towards Scenario Design for Air-Traffic Human-Performance Experiments, IEEE Symposium Series on Computational Intelligence, Singapore.
  26. Halder, K. K., Tahtali, M., and Anavatti, S. G. (2013). High Precision Restoration Method for Non-Uniformly Warped Images. Advanced Concepts for Intelligent Vision Systems. Lecture Notes in Computer Science, 8192.
  27. Hassanein, O, Anavatti S.G. and Tapabrata R. (2013). Black-box Tool for Non-linear System Identification based upon Fuzzy System, International Journal of Computational Intelligence and Applications, 12(02).
  28. Kirsanov, A., Anavatti, S. G., and Ray, T. (2013). 3D tools for the Robust Design Optimization of an Autonomous Underwater Vehicle. Proceedings of the 2013 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2013, India.
  29. Halder, K., Tahtali, M., and Anavatti, S. G. (2013). A Fast Restoration Method for Atmospheric Turbulence Degraded Images Using Non-Rigid Image Registration. Proceedings of the 2013 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2013, India.
  30. Li, C., Anavatti, S., and Ray, T. (2013). A game theory based traffic assignment using queueing networks. 13th International Conference on ITS Telecommunications (ITST 2013), Tampere, Finland.
  31. Halder, K. K., Tahtali, M., and Anavatti, S. G. (2013). An improved restoration method for non-uniformly warped images using optical flow technique. International Conference on Digital Image Computing: Techniques and Applications, DICTA 2013.
  32. Li, C., Anavatt, S. G., and Ray, T. (2013). Application of a non-cooperative game theory based traffic assignment. International Conference on Advances in Computing, Communications and Informatics, ICACCI 2013, India.
  33. Pratama, M., Anavatt, S. G., and Lughofer, E. D. (2013). Evolving Fuzzy Rule-Based Classifier Based on GENEFIS. IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2013). India.
  34. Ray, T., Anavatti, S., and Hassanein, O. (2013). Hybrid Neuro-Fuzzy Network Identification for Autonomous Underwater Vehicles. Swarm, Evolutionary, and Memetic Computing, Lecture Notes in Computer Science, Vol. 8298.
  35. Hassanein, O., Anavatti, S. G., and Ray, T. (2013). On-line adaptive fuzzy modeling and control for autonomous underwater vehicle. Recent Advances in Robotics and Automation (Vol. 480, pp. 57-70). Heidelberg: Springer.
  36. Anavatti, S. G., Ray, T., and Kirsanov, A. (2013). Path Planning for the Autonomous Underwater Vehicle. Swarm, Evolutionary, and Memetic Computing, Lecture Notes in Computer Science, Vol. 8298.
  37. Elsayed, S., Sarker, R. and Essam, D. (2013) An Improved Self-Adaptive Differential Evolution Algorithm for Optimization Problems, IEEE Transactions on Industrial Informatics, 9(1), pp89-99 (Impact Factor: 8.785; ERA A)
  38. Hamza, N., Sarker, R. and Essam, D. (2013) Differential Evolution with Multi-Constraint Consensus Methods for Constrained Optimization, Journal of Global Optimization, 57(2), 583-611. (Impact Factor: 1.287, 2010 ERA A)
  39. Singh, H., Ray, T. and Sarker, R. (2013) Optimum oil production planning using Infeasibility Driven Evolutionary Algorithm, Evolutionary Computation, 21(1), 65-82. (Impact Factor: 2.366, 2010 ERA A)
  40. Elsayed, S., Sarker, R. and Essam, D. (2013) Adaptive Configuration of Evolutionary Algorithms for Constrained Optimization, Applied Mathematics and Computation, 222, pp680-7211 (Impact Factor: 1.551; 2010 ERA A)
  41. Sarker, R., Omar, M., Hasan, S. M. K. and Essam, D. (2013) Hybrid Evolutionary Algorithm for Job Scheduling under Machine Maintenance, Applied Soft Computing, 13(3), pp1440-1447 (Impact Factor: 2.810)
  42. Hishamuddin, H., Sarker, R. and Essam, D. (2013) A Recovery Model for a Two-Echelon Serial Supply Chain with Consideration of Transportation Disruption, Computers and Industrial Engineering, 64(2), pp552-561. (Impact Factor: 1.783)
  43. Omar, M., Sarker, R. and Othman, W. A. M. (2013) A just-in-time three-level integrated manufacturing system for linearly time-varying demand process, Applied Mathematical Modelling, 37(3), 1275-1281 (Impact Factor: 2.251)
  44. Elsayed, S., Sarker, R. and Essam, D. (2013) Self-Adaptive Differential Evolution Incorporating a Heuristic Mixing of Operators, Computational Optimization and Applications, 54(3), 771-790 (Impact Factor: 1.317)
  45. Asafuddoula, A. , Ray, T. and Sarker, R. (2013) A decomposition based evolutionary algorithm for many objective optimization with systematic sampling and adaptive epsilon control, International Conference on Evolutionary Multi-Criterion Optimization, Sheffield, UK, In Press, Lecture Notes in Computer Science, Springer, Volume 7811, pp.413-427.
  46. Paul, S., Sarker, R. and Essam, D. (2013) A Disruption Recovery Model in a Production-Inventory System with Demand Uncertainty and Process Reliability, 12th International Conference on Computer Information Systems and Industrial Management Applications (CISIM 2013), Krakow, Poland, September 25-27, Lecture Notes in Computer Science, Volume 8104, Springer, pp.507-518.
  47. Elsayed, S., Sarker, R. and Mezura-Montes, E. (2013) Particle Swarm Optimizer for Constrained Optimization, IEEE Congress on Evolutionary Computation, Cancun, Mexico, June 20-23, pp2703-2711
  48. Elsayed, S., Sarker, R. and Essam, D. (2013) A Genetic Algorithm for Solving the CEC'2013 Competition Problems on Real-Parameter Optimization, IEEE Congress on Evolutionary Computation, Cancun, Mexico, June 20-23, pp356-360
  49. Elsayed, S., Sarker, R. and Ray, T. (2013) Differential Evolution with Automatic Parameter Configuration for Solving the CEC2013 Competition on Real-Parameter Optimization, IEEE Congress on Evolutionary Computation, Cancun, Mexico, June 20-23, pp1932-1937
  50. Rahman, H. F., Sarker, R. and Essam, D. (2013) A Memetic Algorithm for Permutation Flow Shop Problems, IEEE Congress on Evolutionary Computation, Cancun, Mexico, June 20-23, pp1618-1625
  51. Asafuddoula, M., Ray, T. and Sarker, R. (2013) An Efficient Constraint Handling Approach for Optimization Problems with Limited Feasibility and Computationally Expensive Constraint Evaluations, Genetic and Evolutionary Computation (GECCO™13), July 6“10, 2013, Amsterdam, The Netherlands, pp.113-114.
  52. Elsayed, S. and Sarker, R. (2013) Differential Evolution with Automatic Population Injection Scheme, IEEE Symposium Series on Computational Intelligence 2013, 16-19 April, Singapore, pp112-118.
  53. Asafuddoula, A., Ray, T. and Sarker, R. (2013) Evaluate till you Violate: A Differential Evolution Algorithm Based on Partial Evaluation of the Constraint Set, IEEE Symposium Series on Computational Intelligence 2013, 16-19 April, Singapore, pp31-37.
  54. AbdAllah, A., Essam, D. and Sarker, R. (2013) Using a Diversified Genetic Algorithm to Solve Dynamic Vehicle Routing Problems, Int. Conf. on Artificial Intelligence and Applications, February 11-13, 2013, Innsbruck, Austria, pp9-14.
  55. Paul, S., Sarker, R. and Essam, D. (2013) A Production Inventory Model with Multiple Disruption and Reliability Considerations, Proceedings of the 43rd Conference on Computers & Industrial Engineering, 16-18 October 2013, Hong Kong, pp.117:1-14.
  56. Rahman, H. F., Sarker, R. and Essam, D. (2013) Permutation Flow Shop Scheduling with Dynamic Job Order Arrival, Proceedings of the 6th IEEE International Conference on Cybernetics and Intelligent Systems (CIS™2013), November 12-15, 2013, Manila, Philippines, pp.30-35.
  57. De Silva S, Barlow M, Easton A (2013) Harnessing multi-user design and computation to devise archetypal whole-of-body gestures: a novel framework, 25th Australian Computer-Human Interaction Conference (OzCHI 2013), Adelaide, Australia, 25 Nov 2013 - 29 Nov 2013. Proceedings editors: Shen H, Smith R, Paay J, Calder P, Wyeld T. OzCHI '13 Proceedings of the 25th Australian Computer-Human Interaction Conference: Augmentation, Application, Innovation, Collaboration. 25 Nov 2013
  58. Abdulla U, Taylor K, Barlow MG, Naqshbandi K (2013) Measuring Walking and Running Cadence using Magnetometers, The 12th IEEE International Conference on Ubiquitous Computing and Communications (IUCC-2013), Melbourne, Australia, 16 Jul 2013 - 18 Jul 2013. Proceedings editors: Unknown U. Proceedings of the 12th IEEE International Conference on Ubiquitous Computing and Communications (IUCC-2013). 16 Jul 2013
  59. Lakshika E, Barlow M, Easton A (2013) Co-evolving Semi-competitive Interactions of Sheepdog Herding Behaviors Utilizing a Simple Rule-based Multi Agent Framework, 2013 IEEE Symposium on Artificial Life (ALIFE), 16 Apr 2013 - 19 Apr 2013. Proceedings of 2013 IEEE Symposium on Artificial Life. 05 Apr 2013

2012

  1. M.K.Samal, S.Anavatti and M.Garratt, (2012) Neural network based Model Predictive Controller for Simplified Heave Model of an Unmanned Helicopter,¯ Lecture Notes in Computer Science, vol. 7677, pp. 356“363, 2012.
  2. X.Yang, M.Garratt and H.Pota, (2012) ™Nonlinear Position Control for Hover and Automatic Landing of UAVs,¯ IET Control Theory and Applications, vol. 6, no.7, pp. 911-920, 2012.
  3. T.K.Roy, M.Garratt, H.R.Pota and H.Teimoori, (2012) Robust Backstepping Control for Longitudinal and Lateral Dynamics of Small Scale Helicopter,¯ Journal of University of Science and Technology of China, vol. 42, no. 7, July, 2012.
  4. M.Garratt and S.Anavatti, (2012) Non-linear Control of Heave for an Unmanned Helicopter using a Neural Network,¯ Journal of Intelligent and Robotic Systems, vol. 66, no. 4, pp. 495“504, 2012.
  5. T.K.R.Roy and M.A.Garratt, (2012) Altitude control of an unmanned autonomous helicopter via robust backstepping controller under horizontal wind gusts,¯ In 7th International Conference on Electrical and Computer Engineering (ICECE 2012), Dhaka, Bangladesh, 20“22 Dec 2012.
  6. M.H.Tehrani, M.Garratt and S.Anavatti, (2012) Gyroscope Offset Estimation Using Panoramic Vision-Based Attitude Estimation and Extended Kalman Filter,¯ In 2nd International Conference on Communications, Computing and Control Applications (CCCA12), Marseilles, France, 6“8 Dec 2012.
  7. M.H.Tehrani, M.Garratt and S.Anavatti, (2012) An Accurate Attitude Estimation Using Panoramic Vision and An Extended Kalman Filter,¯ In 3rd World Conference on Information Technology (WCIT-2012), Barcelona, Spain, 14“16 Nov, 2012.
  8. M.K.Samal, S.Anavatti and M.Garratt, (2012) Neural network based Model Predictive Controller for Simplified Heave Model of an Unmanned Helicopter,¯ In Fuzzy and Neural Computing Conference (FANCCO 2012), India, 20“22 Dec 2012.
  9. H.Teimoori, H.R.Pota, M.Garratt and H.Teimoori, (2012) Helicopter Flight Control Using Inverse Optimal Control and Backstepping, ¯ In 12th International Conference on Control, Automation, Robotics and Vision, ICARCV 2012, Guangzhou, China, Dec 5“7, 2012.
  10. M.K.Samal, M.Garratt, H.R.Pota and H.Teimoori, (2012) Model Predictive Flight Controller for Longitudinal and Lateral Cyclic Control of an Unmanned Helicopter,¯ In Australian Control Conference (AUCC 2012), Sydney, Australia, 15“16 Nov 2012.
  11. H.Teimoori, H.R.Pota, M.Garratt and H.Teimoori, (2012) Attitude Control of aMiniature Helicopter using Optimal SlidingMode Control,¯ In Australian Control Conference (AUCC 2012), Sydney, Australia, 15“16 Nov 2012.
  12. S.Francis, S.Anavatti and M.Garratt, (2012) Motion Detection and Velocity Estimation for Obstacle Avoidance using 3D Point Clouds,¯ In 9th International Conference on Informatics in Control, Automation and Robotics (ICINCO), Rome, Italy, 28“31 July, 2012.
  13. S.Francis, S.Anavatti and M.Garratt, (2012) Range based Velocity Estimation Using Scene flow,¯ In 14th International Conference on Artificial Intelligence (ICAI™12) Las Vegas, USA, 16“19 July 2012.
  14. T.K.Roy, H.R.Pota, M.Garratt and H. Teimoori, (2012) Robust Control for Longitudinal and Lateral Dynamics of Small Scale Helicopter,¯ In The 31st Chinese Control Conference (CCC), Hefei, China, pp. 2607-2612, 25“27 Jul 2012.
  15. T.K.Roy, H.R.Pota, M.Garratt and H. Teimoori, (2012) Hover Flight Control of a Small Helicopter Using Robust Backstepping and PID,¯ In 10th World Congress on Intelligent Control and Automation (WCICA), Beijing, China, pp.1688“1693, 6“8 Jul 2012.
  16. T.K.Roy, H.R.Pota, M.Garratt and H. Teimoori, (2012) Robust Altitude Control of an Unmanned Autonomous Helicopter Using Backstepping,¯ In 10th World Congress on Intelligent Control and Automation (WCICA), Beijing, China, pp.1650“1654, 6“8 Jul 2012.
  17. T.K.Roy, H.R.Pota, M.Garratt and M.K.Samal, (2012) Robust Altitude Control for a Small Helicopter by Considering the Ground Effect Compensation,¯ In 10th World Congress on Intelligent Control and Automation (WCICA), Beijing, China, pp.1796“1800, 6“8 Jul 2012.
  18. S.Francis, S.Anavatti and M.Garratt, (2012) D* lite Search algorithm with Fibonacci heap for Efficient Path Planning,¯ In Advances in Control and Optimisation of Dynamical Systems, ACODS2012, Bangalore, India, 16“18 Feb 2012.
  19. M.H.Tehrani, M.Garratt and S.Anavatti, (2012) Horizon-Based Attitude Estimation from a Panoramic Vision Sensor,¯ In Embedded Guidance, Navigation and Control in Aerospace, EGNCA-2012, Bangalore, India, 13“15 Feb 2012.
  20. Macindoe, O., Maher, M.L., Merrick, K.: (2012) Agent Based Intrinsically Motivated Intelligent Environments, in Laurence T. Yang, Evi Syukur, Seng W. Loke (Eds) Handbook on Mobile and Ubiquitous Computing: Innovations and Perspectives, CRC Press Taylors & Francis Group, Auerbach. pp 165-202, ISBN: 978-1-439-84811-1.
  21. Merrick, K.: (2012) Intrinsic Motivation and Introspection in Reinforcement Learning, IEEE Transactions on Autonomous Mental Development , Zhengyou Zhang (Ed), 4(4):315-329.
  22. Shafi, K., Merrick, K., Debie, E.: (2012) Evolution of Intrinsic Motives in Multi-Agent Simulations, The Ninth International Conference on Simulated Evolution and Learning, pp 198-207.
  23. Wang, B., Merrick, K., Abbass, H.: (2012) Developing Attention Focus Metrics for Autonomous Hypothesis Generation in Data Mining, The Ninth International Conference on Simulated Evolution and Learning, pp 290-299.
  24. Hardhienata, M., Merrick, K., Ugrinovskii, V.: (2012) Task Allocation in Multi-Agent Systems using Models of Motivation and Leadership,IEEE Conference on Evolutionary Computation, Brisbane, Australia, pp 86-93. [Nominated for best paper award]
  25. Shafi K., Bender A., Zhong W., and Abbass H.A. (2012) Spatio-Temporal Dynamics of Security Investments in an Interdependent Risk Environment, Physica A: Statistical Mechanics and its Applications, 391(20), 5004-5017
  26. Liu J., Abbass H.A., Green D.G., Zhong W. (2012) Motif Difficulty (MD): A Novel Predictive Measure of Problem Difficulty for Evolutionary Algorithms based on Network Motifs, Evolutionary Computation, MIT Press, 20(3), 1-27.
  27. Alam S., Zhao W., Tang J., Lokan C., Ellejmi M., Kirby S. and Abbass H.A. (2012) A Co-Evolutionary Framework for Identifying Delay Patterns in Arrival Traffic and Ground Events for Dynamic CDA Operations, Air Traffic Control Quarterly, 20(1), 47-72.
  28. Tang J., Alam S., Lokan C. and Abbass H.A. (2012) A Multi-Objective Approach for Dynamic Airspace Sectorization Using Agent Based and Geometric Models, Transportation Research Part C, Elsevier, 21(1), 89-121.
  29. Leu G., Curtis N., and Abbass H.A. (2012) Modeling and Evolving Human Behaviors and Emotions in Road Traffic Networks, Procedia Social and Behavioral Sciences, Elsevier, Vol 54, 999-1009.
  30. Bui V., Pham V.V., Iorio A.W., Tang J., Alam S. and Abbass H.A. (2012) Bio-Inspired Robotics for Air Traffic Weather Information Management, The Transactions of the Institute of Measurement and Control, Sage, 34(2-3), 291-317.
  31. Bui L., Abbass H.A., Barlow M., and Bender A. (2012) Robustness Against the Decision-Maker's Attitude to Risk in Problems with Conflicting Objectives, IEEE Transactions on Evolutionary Computation, 16(1), 1-19.
  32. Ren S., Barlow M., and Abbass H.A. (2012) Frontal Cortex Neural Activities Shift Cognitive Resources Away from Facial Activities, 19th International Conference on Neural Information Processing (ICONIP2012), LNCS766, 132-139, Springer.
  33. Mount W., TuĨek D. and Abbass H.A. (2012) A Psychophysiological Analysis of Weak Annoyances in Human Computer Interfaces, 19th International Conference on Neural Information Processing (ICONIP2012), LNCS7663, 202-209, Springer.
  34. TuĨek D., Mount W. and Abbass H.A. (2012) Neural and Speech Indicators of Cognitive Load for Sudoku Game Interfaces, 19th International Conference on Neural Information Processing (ICONIP2012), LNCS7663, 210-217, Springer.
  35. Mount W., TuĨek D. and Abbass H.A. (2012) Psychophysiological Evaluation of Task Complexity and Cognitive Performance in a Human Computer Interface Experiment, 19th International Conference on Neural Information Processing (ICONIP2012), LNCS7663, 600-607, Springer.
  36. Zhang B., Shafi K., and Abbass H.A. (2012) Density Based Multi-Objective Optimization for Smart Distribution Grid Design, Ninth International Conference on Simulated Evolution and Learning (SEAL2012), LNCS, Springer.
  37. Wang B., Merrick K.E., Abbass H.A. (2012) Developing Attention Focus Metrics for Autonomous Hypotheses Generation in Data Mining, Ninth International Conference on Simulated Evolution and Learning (SEAL2012), LNCS, Springer.
  38. Shafi K., Bender A., and Abbass H.A. (2012) Multi Objective Learning Classifier Systems Based Hyperheuristics for Modularised Fleet Mix Problem, Ninth International Conference on Simulated Evolution and Learning (SEAL2012), LNCS, Springer.
  39. Vu C.C., Bui L.T., and Abbass H.A. (2012) DEAL: A Direction-guided Evolutionary Algorithm, Ninth International Conference on Simulated Evolution and Learning (SEAL2012), LNCS, Springer.
  40. Wang K., Bui V., Petraki E., and Abbass H.A. (2012) From subjective to objective metrics for evolutionary story narration using event permutations, Ninth International Conference on Simulated Evolution and Learning (SEAL2012), LNCS, Springer.
  41. Alam S., Lokan C., and Abbass H.A. (2012) What can make an airspace unsafe? Characterizing collision risk using multi-objective optimization, IEEE Congress on Evolutionary Computation, Brisbane, Australia.
  42. Bui V., Bender A. and Abbass H.A. (2012) An Expressive GL-2 Grammar for Representing Story-like Scenarios, IEEE Congress on Evolutionary Computation, Brisbane, Australia.
  43. Tang J., Alam S., Lokan C. and Abbass H.A. (2012) A Multi-objective Evolutionary Method for Dynamic Airspace Re-sectorization using Sectors Clipping and Similarities. IEEE Congress on Evolutionary Computation, Brisbane, Australia.
  44. Xiong J., Shafi K. and Abbass H.A. (2012) Multi-Uncertainty Problems (MUP) with Applications to Managing Risk in Resource-Constrained Project Scheduling. IEEE Congress on Evolutionary Computation, , Brisbane, Australia.
  45. Alam, K., Ray, T., and Anavatti, S. G. (2012). A new robust design optimization approach for unmanned underwater vehicle design. Proceedings of the Institution of Mechanical Engineers, Part M: Journal of Engineering for the Maritime Environment, 226(3).
  46. Alam., Ray, T., and Sreenatha, A. G. (2012). A Study on the Drag Estimation of an AUV Based on Numerical Methods. Proceedings of Advances in Control and Optimization of Dynamical Systems, ACODS-2012, India.
  47. Li, C., Sreenatha, A. G., and Ray, T. (2012). Adaptive Route Guidance System with Real-Time Traffic Information. Proceedings of 15th International IEEE Conference on Intelligent Transportation Systems , Anchorage, Alaska, USA.
  48. Li, C., Sreenatha, A. G., and Ray, T. (2012). An AHP-Fuzzy approach for incorporation of driver™s requirement in route guidance system. Proceedings of Advances in Control and Optimization of Dynamical Systems, ACODS-2012, India.
  49. Alam., Ray, T., and Sreenatha, A. G. (2012). An Evolutionary Approach for the Design of Autonomous Underwater Vehicles. Lecture Notes in Computer Science, 7691, Springer.
  50. Hassan, O., Sreenatha, A. G., and Ray, T. (2012). ANFN Controller Based On Differential Evolution for Autonomous Underwater Vehicles. First International Conference on Innovative Engineering Systems (ICIES) (pp. 184-189). Alex-Egypt: IEEE.
  51. Sobers, F., Sreenatha, A. G., and Garratt, M. A. (2012). D* lite Search algorithm with Fibonacci heap for Efficient Path Planning. 2nd International Conference of Advances in Control and Optimization of Dynamical Systems, ACODS 2012, India.
  52. Salman, S. A., and Anavatti, S. G. (2012). Fuzzy model based control of unmanned aerial vehicle. In IFAC Proceedings Volumes (IFAC-PapersOnline) Vol. 1, India.
  53. Li, C., Anavatti, S. G., and Ray, T. (2012). Implementing analytical hierarchy process using fuzzy inference technique in route guidance system. Proceedings of the 2012 International Conference on Artificial Intelligence, ICAI 2012.
  54. Hassan, O., Sreenatha, A. G., and Ray, T. (2012). Improved Fuzzy Neural Modeling Based on Differential Evolution for Underwater Vehicles. International Conference on Artificial Intelligence ICAI'12 (pp. 984-990). Las Vegas, USA.
  55. Hassan, O., Sreenatha, A. G., and Ray, T. (2012). Improved Fuzzy Neural Modeling for Underwater Vehicles. World Academy of Science, Engineering and Technology, Nov. 2012(71).
  56. Sobers, F., Sreenatha, A. G., and Garratt, M. A. (2012). Motion Detection and Velocity Estimation for Obstacle Avoidance using 3D Point Clouds ICINCO 2012 - Proceedings of the 9th International Conference on Informatics in Control, Automation and Robotics, pp. 255 “ 259
  57. Kallapur, A. G., Petersen, I. R., and Sreenatha, A. G. (2012). Robust Gyro-free Attitude Estimation for a Small Fixed-wing Unmanned Aerial Vehicle. Asian Journal of Control, 14(6).
  58. Barkat Ullah, A., Sarker, R. and Lokan, C. (2012) Handling Equality Constraints in Evolutionary Optimization, European Journal of Operational Research, 221(3), 480-490 (Impact Factor: 2.358, 2010 ERA A)
  59. Naznin, F., Sarker, R. and Essam, D. (2012) Progressive Alignment Method using Genetic Algorithm for Multiple Sequence Alignment, IEEE Transactions on Evolutionary Computation, 16(5), 615-631 (Impact Factor: 3.654, 2010 ERA A*)
  60. Hishamuddin, H., Sarker, R. and Essam, D. (2012) A Disruption Recovery Model for a Single Stage Production-Inventory System, European Journal of Operational Research, 222(3), 464-473 (Impact Factor: 2.358, 2010 ERA A)
  61. Elsayed, E., Sarker, R. and Essam, D. (2012) On an Evolutionary Approach for Constrained Optimization Problem Solving, Applied Soft Computing, 12(10), 3208-3227 (Impact Factor: 2.810)
  62. Ray, T. and Sarker, R. (2012) Memetic Algorithms in Constrained Optimization, Handbook of Memetic Algorithms, Studies in Computational Intelligence, Volume 379/2012, Springer, 135-151.
  63. Elsayed, S., Sarker, R. and Essam, D. (2012) The Influence of the Number of Initial Feasible Solutions on the Performance of an Evolutionary Optimization Algorithm, In Simulated Evolution And Learning, Lecture Notes in Computer Science, Springer, Volume 7673, pp1-11.
  64. Sayed, E., Essam, D. and Sarker, R. (2012) Using Hybrid Dependency Identification with a Memetic Algorithm for Large Scale Optimization Problems, In Simulated Evolution And Learning, Lecture Notes in Computer Science, Springer, Volume 7673, pp168-177.
  65. Asafuddoula, A., Ray, T. and Sarker, R. (2012) A self-adaptive differential evolution algorithm with constraint sequencing, in Proceedings of the Australasian Joint Conference on Artificial Intelligence, (Sydney, Australia), Lecture Notes in Computer Science, Springer, Volume 7691, pp182-193.
  66. Sayed, E., Sarker, R. and Essam, D. (2012) Dependency Identification Technique for Large Scale Optimization Problems, IEEE Congress on Evolutionary Computation, World Congress on Computational Intelligence (WCCI2012), Brisbane, June 10-15, pp.1-8.
  67. Elsayed, S., Sarker, R. and Essam, D. (2012) Memetic Multi-Topology Particle Swarm Optimizer for Constrained Optimization, IEEE Congress on Evolutionary Computation, World Congress on Computational Intelligence (WCCI2012), Brisbane, June 10-15, pp.1-8.
  68. Elsayed, S., Sarker, R. and Ray, T. (2012) Parameters Adaptation in Differential Evolution, IEEE Congress on Evolutionary Computation, World Congress on Computational Intelligence (WCCI2012), Brisbane, June 10-15pp.1-8.
  69. Hazma, N., Sarker, R. and Essam, D. (2012) Differential Evolution with a mix of Constraint Consensus Methods for Solving a Real-World Optimization Problem, IEEE Congress on Evolutionary Computation, World Congress on Computational Intelligence (WCCI2012), Brisbane, June 10-15, pp.1-7.
  70. Asafuddoula, A., Ray, T. and Sarker, R. (2012) An Adaptive Constraint Handling Approach Embedded MOEA/D, IEEE Congress on Evolutionary Computation, World Congress on Computational Intelligence (WCCI2012), Brisbane, June 10-15, pp.1-8.
  71. Lakshika E, Barlow MG, Easton AC (2012) Fidelity and complexity of standing group conversation simulations: a framework for the evolution of Multi Agent Systems through bootstrapping human aesthetic judgments, 2012 IEEE Congress on Evolutionary Computation (CEC), Brisbane, QLD, 10 Jun 2012 - 15 Jun 2012. Evolutionary Computation (CEC), 2012 IEEE Congress on. IEEE Press, USA. 8 pp.. 2012
  72. Barlow M, Rowlands E (2012) Quantification of game ai performance for junior leadership training in the defence domain, Proceedings of SimTecT 2012.