A/Prof Peter Vamplew - Research

Graduate research supervisions

I have supervised more than ten students to successful PhD and Masters completions in topics including artificial intelligence, reinforcement learning, video games and cybersecurity.

Currently I am primary supervisor for the following students, in addition to being associate supervisor for several others:

  • Budi Kurniawan - Multi-Objective Reinforcement Learning in Dynamic Team Based Adversarial Games
  • Charlotte Young – Assessing the Explainability of XAI Systems
  • Alastair Lansley – New Wave Input: An Exploration of Novel Input Technologies and their Uses
  • Amy Meade – Developing a Framework for Educational Use of Mixed Reality

Current research projects

Ongoing research projects relating to the development and application of multiobjective reinforcement learning algorithms, including to areas such as explainability and safety of autonomous AI systems.

Publications/conferences

Journal papers

  1. Khraisat, A., Gondal, I., Vamplew, P. , Kamruzzaman, J. and Alazab, A. (2020), Hybrid Intrusion Detection System Based on the Stacking Ensemble of C5 Decision Tree Classifier and One Class Support Vector Machine, Electronics, 9(1).
  2. Vamplew, P. , Foale, C. and Dazeley, R. (2020), A Demonstration of Issues with Value-Based Multiobjective Reinforcement Learning Under Stochastic State Transitions, Adaptive and Learning Agents Workshop at AAMAS2020: International Conference on Autonomous Agents and Multi-Agent Systems, Auckland, New Zealand, May 2020.
  3. Kurniawan, B., Vamplew, P. , Papasimeon, M., Dazeley, R. and Foale, C. (2020), Discrete-to-Deep Supervised Policy Learning: An effective training method for neural reinforcement learning, Adaptive and Learning Agents Workshop at AAMAS2020: International Conference on Autonomous Agents and Multi-Agent Systems, Auckland, New Zealand, May 2020.
  4. Ul Haq, I., Gondal, I. and Vamplew, P. (2020), Enhancing Model Performance for Fraud Detection by Feature Engineering and Compact Unified Expressions, 19th International Conference on Algorithms and Architectures for Parallel Processing Melbourne, Australia | 9-11 Dec 2019.
  5. Greenwood, J., Achterbosch, L., Meredith, G. and Vamplew, P. (2020), Motivational Factors of Australian Mobile Gamers, Interactive Entertainment: The 16th annual Australasian conference on interactive digital media design and technologies, Melbourne, February 2020.
  6. Kurniawan, B., Vamplew, P. , Papasimeon, M., Dazeley, R. and Foale, C. (2019), An Empirical Study of Reward Structures for Actor-Critic Reinforcement Learning in Air Combat Manoeuvring Simulation, Australasian Joint Conference on Artificial Intelligence, Adelaide, December 2019.
  7. Cruz, F., Dazeley, R. and Vamplew, P. (2019), Memory-based Explainable Reinforcement Learning, Australasian Joint Conference on Artificial Intelligence, Adelaide, December 2019.
  8. Zarnegar, A., Jelinek, H., Vamplew, P. and Stranieri, A. (2019), Integrating Biological Heuristics and Gene Expression Data for Gene Regulatory Network Inference, 11th Australasian Conference on Health Informatics and Knowledge Management, Sydney, January 2019.
  9. Black, P., Gondal, I., Vamplew, P. and Lakhotia, A. (2019), Evolved Similarity Techniques in Malware Analysis, TrustCom: 18th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, Rotorua, New Zealand, August 2019.
  10. Khraisat, A., Gondal, I., Vamplew, P. and Kamruzzaman, J. (2019), A Novel Ensemble of Hybrid Intrusion Detection System for Detecting Internet of Things Attacks, Electronics, Special Issue on Machine Learning Techniques for Intelligent Intrusion Detection Systems.
  11. Khraisat, A., Gondal, I., Vamplew, P. and Kamruzzaman, J. (2019), Survey of Intrusion Detection Systems: Techniques, Datasets and Challenges, Cybersecurity
  12. Vamplew, P., Dazeley, R., Foale, C. and Choudhury, T., (2018), Non-Functional Regression: A New Challenge for Neural Networks, Neurocomputing, 314, 326-335.
  13. Lansley, A., Vamplew, P., Foale, C. and Smith, P. (2018), SoniFight: Software to provide additional sonification cues to video games for visually impaired players, The Computer Games Journal, 7(2), 115-130.
  14. Achterbosch, L., Miller, C., & Vamplew, P (2018). Participant observation of griefing in a journey through the World of Warcraft. Loading… The Journal of the Canadian Game Studies Association 10 (17), 40-59
  15. Vamplew, P., Dazeley, R., Foale, C., Firmin, S., & Mummery, J. (2018). Human-aligned artificial intelligence is a multiobjective problem. Ethics and Information Technology, 20 (1), 27-40.
  16. Achterbosch, L., Miller, C. and Vamplew, P. (2017), A taxonomy of griefer type by motivation in massively multiplayer online role-playing games, Behaviour and Information Technology, 36 (8), 846-860.
  17. Vamplew, P., Dazeley, R. and Foale, C., (2017), Softmax Exploration Strategies for Multiobjective Reinforcement Learning, Neurocomputing, 263, 74-86
  18. Vamplew, P., Issabekov, R., Dazeley, R., Foale, C., Berry, A., Moore, T. and Creighton, D. (2017), Steering Approaches to Pareto-Optimal Multiobjective Reinforcement Learning, Neurocomputing, 263, 26-38
  19. Lansley, A, Vamplew, P, Smith, P and Foale, C (2016) Caliko: An Inverse Kinematics Software Library Implementation of the FABRIK Algorithm. Journal of Open Research Software, 4: e36, DOI: http://dx.doi.org/10.5334/jors.116
  20. Wang, J., Lim, C.P., Creighton, D., Khorsavi, A., Nahavandi, S., Ugon, J., Vamplew, P., Stranieri, A., Martin, L. and Freischmidt, A. (2015), Patient admission prediction using a pruned fuzzy min-max neural network with rule extraction, Neural Computing and Applications, 26(2), 277-289.
  21. Ross, J., Miller, C. and Vamplew, P. (2014), Video games classified M and MA15+ in Australia compared with their international counterparts: does games classification protect Australian children?, Journal of Research and Practice in Information Technology, accepted for publication.
  22. Achterbosch, L., Miller, C., Turville, C. and Vamplew, P. (2014), Griefers versus the Griefed - what motivates them to play Massively Multiplayer Online Role-Playing Games?, The Computer Games Journal, 3(1), Candlemas 2014, 5-18.
  23. Roijers, D., Vamplew, P., Whiteson, S. and Dazeley, R. (2013), A Survey of Multiobjective Sequential Decision-Making, Journal of Artificial Intelligence Research, Vol 48, 67-113.
  24. Torney, R., Vamplew, P. and Yearwood, J. (2012), Using Psycholinguistic Features for Profiling First Language of Authors, Journal of the American Society for Information Science and Technology, 63(6), 1256-1269.
  25. Moloney, D., Sukhorukova, N., Vamplew, P., Ugon, J., Li, G., Beliakov, G., Philippe, C., Amiel, H. and Ugon, A. (2011), Detecting K-complexes for sleep stage identification using nonsmooth optimisation, Australia and New Zealand Journal of Industrial and Applied Mathematics, Vol 52, No 4, 319-332.
  26. Kelarev, A., Yearwood, J.L., Vamplew, P. W., Abawajy, J. And Chowdhury, M. (2011), Optimization and Matrix Constructions for Classification of Data, New Zealand Journal of Mathematics, 41, 65-73.
  27. Vamplew, P., Dazeley, R., Berry, A., Dekker, E. and Issabekov, R. (2011) Empirical Evaluation Methods for Multiobjective Reinforcement Learning Algorithms, Machine Learning, Special Issue on Empirical Evaluations in Reinforcement Learning, 84(1-2): 51-80.
  28. Osman, D., Yearwood, J. and Vamplew, P. (2010), "Automated Opinion Detection: Implications of the Level of Agreement Between Human Raters", Information Processing and Management, 46(3), pp 331-342.
  29. Osman, D., Yearwood, J. and Vamplew, P. (2009), "Weblogs for Market Research: Finding More Relevant Opinion Documents using System Fusion", in Journal of Online Information Review, Special Issue on Web Mining for E-Commerce and E-Services, 33(5), pp 873-888.
  30. Kelarev, A.V., Yearwood, J.L., Vamplew, P.W. (2009) "A polynomial ring construction for classification of data", Bulletin of the Australian Mathematical Society , 79, pp 213-225.
  31. Johnson, D, Malhotra, V, & Vamplew, P (2006), "More Effective Web Search Using Bigrams and Trigrams." Webology, 3(4), Article 35.
  32. Ollington, R and Vamplew, P, (2005) "Concurrent Q-Learning: Reinforcement Learning for Dynamic Goals and Environments", International Journal of Intelligent Systems, Vol 20, Issue 10, October 2005, pp 1037-1052
  33. Ollington, R and Vamplew, P, (2002) "A Supervised Neural Network Based on the Cerebellum", Australian Journal of Intelligent Information Processing Systems, Vol 6, No. 4, Summer 2000, pp242-248 (actually published in 2002)
  34. Adams, A and Vamplew, P, (1998) "Encoding and Decoding Cyclic Data", The South Pacific Journal of Natural Science, Vol 16, pp. 54-58
  35. Vamplew, P and Adams, A, (1998) "Recognition of Sign Language Gestures Using Neural Networks", Australian Journal of Intelligent Information Processing Systems, Vol 5, No. 2, pp.94-102

Book chapters

  1. Block, J., Graymore, M., Wallis, A. M., Vamplew, P., Mitchell, B., O'Toole, K. and McRae-Williams, P. (2012). Visualising the Value of Water. In M. Graymore, P. McRae-Williams, Barton, A. and L. Lehmann (Eds.) Pipes, Ponds and People: Adaptive water management in Drylands. VURRN Press, Mt Helen, Victoria
  2. Torney, R., Yearwood, J., Vamplew, P. and Kelarev, A. (2012), "Applications of Machine Learning for Linguistic Analysis of Texts" in Kulkarni, S. (eds), Machine Learning Algorithms for Problem Solving in Computational Applications: Intelligent Techniques, IGI Global, 133-148.
  3. Ollington, R., Vamplew, P. and Swanson, J. (2009), "Incorporating Expert Advice into Reinforcement Learning Using Constructive Neural Networks", in Franco, L., Elizondo, D. and Jerez, J.M. (eds), "Constructive Neural Networks", Studies in Computational Intelligence Vol. 258, Springer, ISBN 978-3-642-04511-0, pp 207-224.
  4. Vamplew, P (2002), "Websites", in Cox, R, Russell, D and Vamplew, W (eds), "The Encyclopedia of British Football", Frank Cass, pp 318-320
  5. Vamplew, P (1994), "Sign Language Recognition Using Virtual Reality Gloves" in Loeffler, CE and Anderson, T (eds),  "Virtual Reality Casebook", Van Nostrand Reinhold, pp 123-126 [also published in Japanese as  Loeffler, CE, "Virtual Realities: Anthology of Industry and Culture", Gijitsu Hyoron Sha, Tokyo, 1993, pp 210-214]

Book chapters

  1. Achterbosch, L. and Vamplew, P. (2018), Griefing in MMORPGs, in Lee, N. (ed.), Encyclopedia of Computer Graphics and Games, Springer,
    DOI: https://doi.org/10.1007/978-3-319-08234-9_200-1
  2. Block, J., Graymore, M., Wallis, A. M., Vamplew, P., Mitchell, B., O'Toole, K. and McRae-Williams, P. (2012). Visualising the Value of Water. In M. Graymore, P. McRae-Williams, Barton, A. and L. Lehmann (Eds.) Pipes, Ponds and People: Adaptive water management in Drylands. VURRN Press, Mt Helen, Victoria
  3. Torney, R., Yearwood, J., Vamplew, P. and Kelarev, A. (2012), "Applications of Machine Learning for Linguistic Analysis of Texts" in Kulkarni, S. (eds), Machine Learning Algorithms for Problem Solving in Computational Applications: Intelligent Techniques, IGI Global, 133-148.
  4. Ollington, R., Vamplew, P. and Swanson, J. (2009), "Incorporating Expert Advice into Reinforcement Learning Using Constructive Neural Networks", in Franco, L., Elizondo, D. and Jerez, J.M. (eds), "Constructive Neural Networks", Studies in Computational Intelligence Vol. 258, Springer, ISBN 978-3-642-04511-0, pp 207-224.
  5. Vamplew, P (2002), "Websites", in Cox, R, Russell, D and Vamplew, W (eds), "The Encyclopedia of British Football", Frank Cass, pp 318-320
  6. Vamplew, P (1994), "Sign Language Recognition Using Virtual Reality Gloves" in Loeffler, CE and Anderson, T (eds), "Virtual Reality Casebook", Van Nostrand Reinhold, pp 123-126 [also published in Japanese as Loeffler, CE, "Virtual Realities: Anthology of Industry and Culture", Gijitsu Hyoron Sha, Tokyo, 1993, pp 210-214]

International conference papers

  1. Maruatona, O., Vamplew, P., Dazeley, R. and Watters, P. (2017), Evaluating Accuracy in Prudence Analysis for Cyber Security, 24th International Conference on Neural Information Processing (ICONIP 2017).
  2. Sharma, V., Stranieri, A., Ugon, J., Vamplew, P. and Martin, L., (2017), An Agile Group Aware Process beyond CRISP-DM: A Hospital Data Mining Case Study, International Conference On Computing and Data Analysis, Florida, May 2017.
  3. Zarnegar, A., Vamplew, P., Stranieri, A., & Jelinek, H. F. (2016), A Heuristic Gene Regulatory Networks Model for Cardiac Function and Pathology, Computing in Cardiology Conference, Vancouver, Canada, September 2016.
  4. Roijers, D., Whiteson, S., Vamplew, P. and Dazeley, R. (2015), Why Multi-objective Reinforcement Learning?, European Workshop on Reinforcement Learning.
  5. Maruatona, O., Vamplew, P. and Dazeley, R. (2012), RM and RDM, a Preliminary Evaluation of Two Prudent RDR Techniques, 12th Pacific Rim Knowledge Acquisition Workshop, Lecture Notes in Computer Science Volume 7457, Springer, pp 188-194.
  6. Mukherjee, S.; Yearwood, J.; Vamplew, P. and Huda, S. (2011), Reinforcement Learning Approach to AIBO Robot's Decision Making Process in Robosoccer's Goal Keeper Problem in Proceedings of 12th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, pp 24-30.
  7. Dazeley, R., Warner, P., Johnson, S. and Vamplew, P. (2010) The Ballarat Incremental Knowledge Engine, In the 11th International Workshop on Knowledge Management and Acquisition for Smart Systems and Services (PKAW 2010)
  8. Islam, M., Yearwood, J., Vamplew, P. (2008), Unsupervised Segmentation of Industrial Images Using Markov Random Field Model, in Proceedings of the International Joint Conferences on Computer, Information, and Systems Sciences, and Engineering 2008 (CISSE 2008).
  9. Islam, M., Yearwood, J., Vamplew, P. (2008), MRF Model Based Unsupervised Color Textured Image Segmentation Using Multidimensional Spatially Variant Finite Mixture Model, in Proceedings of the International Joint Conferences on Computer, Information, and Systems Sciences, and Engineering 2008 (CISSE 2008).
  10. Osman, D., Yearwood, J. and Vamplew, P. (2008), "System Fusion for Opinion Detection in Weblogs", 2nd International Workshop on Web Mining for E-commerce and E-services (WMEE' 08), Melbourne.
  11. Islam, M., Yearwood, J., and Vamplew, P. (2007), Unsupervised Color Textured Image Segmentation Using Cluster Ensemble and MRF Model, International Joint Conferences on Computer, Information, and Systems Sciences, and Engineering, IEEE Proceedings, Springer, Berlin.
  12. Berry, A. and Vamplew, P.W. (2006), "An Efficient Data Structure for Unbounded Bi-Objective Archives - Introducing the Mak_Tree", at GECCO-2006: The Genetic and Evolutionary Computation Conference.
  13. Vamplew, P and Ollington, R, (2005), "On-Line Reinforcement Learning Using Cascade Constructive Neural Networks", in Khosla, R., Howlett, R.J. and Jain, L.J. (Eds.), Proceedings of  KES2005: Ninth International Conference on Knowledge-Based Intelligent Information & Engineering Systems Part III, Lecture Notes in Artificial Intelligence 3683, Springer, Berlin, 2005, ISBN 3-5440-28896-1, pp 562-568.
  14. Berry, A. and Vamplew, P.W. (2005), "The Combative Accretion Model: Multiobjective Optimisation Without Explicit Pareto Ranking", in Carlos A. Coello Coello, Arturo Hernández Aguirre, Eckart Zitzler (Eds.): Evolutionary Multi-Criterion Optimization, Third International Conference,EMO 2005, Guanajuato, Mexico, March 9-11, 2005, Proceedings. Lecture Notes in Computer Science 3410 Springer 2005, ISBN 3-540-24983-4, pp 77-91.
  15. Vamplew, P.W. (2004), "Lego? Mindstorms? Robots as a Platform for Teaching Reinforcement Learning", in Negnevitsky, M (ed), Proceedings of AISAT2004: International Conference on Artificial Intelligence in Science and Technology, University of Tasmania, Hobart, Australia, November 2004, ISBN 1862952094, pp 70-75.
  16. Ollington, R. B. and Vamplew, P.W. (2004), "Learning Place Cells from Sonar Data", in Negnevitsky, M (ed), Proceedings of AISAT2004: International Conference on Artificial Intelligence in Science and Technology, University of Tasmania, Hobart, Australia, November 2004, ISBN 1862952094, pp 126-131
  17. Ollington, R.B. and Vamplew, P.W. (2004), "Reducing the Time Complexity of Goal-Independent Reinforcement Learning", in Negnevitsky, M (ed), Proceedings of AISAT2004: International Conference on Artificial Intelligence in Science and Technology, University of Tasmania, Hobart, Australia, November 2004, ISBN 1862952094, pp 132-137
  18. Berry, A. and Vamplew, P.W. (2004), "A Language for Platform Independent Communication and Storage in Multiobjective Optimisation", in Negnevitsky, M (ed), Proceedings of AISAT2004: International Conference on Artificial Intelligence in Science and Technology, University of Tasmania, Hobart, Australia, November 2004, ISBN 1862952094, pp 308-313
  19. Berry, A. and Vamplew, P.W. (2004), "PoD Can Mutate: A Simple Dynamic Directed Mutation Approach for Genetic Algorithms", in Negnevitsky, M (ed), Proceedings of AISAT2004: International Conference on Artificial Intelligence in Science and Technology, University of Tasmania, Hobart, Australia, November 2004, ISBN 1862952094, pp 200-205
  20. Field, T. and Vamplew, P.W. (2004), "Generalised Algorithms for Redirected Walking in Virtual Environments", in Negnevitsky, M (ed), Proceedings of AISAT2004: International Conference on Artificial Intelligence in Science and Technology, University of Tasmania, Hobart, Australia, November 2004, ISBN 1862952094, pp 58-63
  21. Johnson, D., Malhotra, V.M., Vamplew, P.W., and Patro, S. (2004), "Refining Search Queries From Examples Using Boolean Expressions and Latent Semantic Analysis". in Negnevitsky, M (ed), Proceedings of AISAT2004: International Conference on Artificial Intelligence in Science and Technology, University of Tasmania, Hobart, Australia, November 2004, ISBN 1862952094, pp 120-125
  22. Ollington, R. and Vamplew, P. (2003), "Concurrent Q-Learning for Autonomous Mapping and Navigation" at the 2nd International Conference on Computational Intelligence, Robotics and Autonomous Systems, Singapore, 15-18 December 2003.
  23. Ollington, R. and Vamplew, P. (2003), "Adaptive Response Function Neurons" at the 2nd International Conference on Computational Intelligence, Robotics and Autonomous Systems, Singapore, 15-18 December 2003.
  24. Berry, A. and Vamplew, P. (2003), "A Simplified Artificial Life Model for Multiobjective Optimisation: A Preliminary Report", in Proceedings of the 2003 Congress on Evolutionary Computation (CEC'2003), Volume 2, pp. 1331--1339, IEEE Press, Canberra, Australia, December 2003 .
  25. Rosebrock, U and Vamplew, P, (1999) "The intent to move; generating spatial memory in Virtual Environments", at the 5th International Conference on Virtual Systems and Multimedia, Dundee, Scotland, 1-2 September 1999
  26. Vamplew, P (1996), "Recognition of Sign Language Gestures Using Neural Networks", in Sharkey, P (ed), Proceedings of the 1st European Conference on Disabilities, Virtual Reality and Associated Technologies, University of Reading, UK, 1996, ISBN 0-7049-1140-X, pp 27-34.
  27. Vamplew, P and Adams, A (1995), "Recognition and Anticipation of Hand Motions Using a Recurrent Neural Network" at IEEE International Conference on Neural Networks, Perth, Western Australia, 27 November - 1 December 1995, pp 2904-2907
  28. Adams, A, Bye, S and Vamplew, P (1992), "A New Artificial Neural Network Classifier", at ICANN 92: The International Conference on Artificial Neural Networks, Brighton, UK, 4-7 September 1992
  29. Vamplew, P and Adams, A (1992), "The SLARTI System: Applying Artificial Neural Networks to Sign Language Recognition" at The Conference on Technology and Persons with Disabilities, California State University, Northridge, 18-21 March, 1992, pp 575-580.

Australian conference papers

  1. Zarnegar, A., Jelinek, H., Vamplew, P. and Stranieri, A. (2019), Integrating Biological Heuristics and Gene Expression Data for Gene Regulatory Network Inference, 11th Australasian Conference on Health Informatics and Knowledge Management, Sydney, January 2019.
  2. Ul Haq, I., Gondal, I. and Vamplew, P. (2018), Categorical Features Transformation with Compact One-hot Encoder for Fraud Detection in Distributed Environment, 16th Australasian Data Mining Conference, Bathurst, November 2018.
  3. Khraisat, A., Gondal, I. and Vamplew, P. (2018), An Anomaly Intrusion Detection System Using C5 Decision Tree Classifier, Australasian Workshop on Machine Learning for Cyber-security, The 22nd Pacific-Asia Conference on Knowledge Discovery and Data Mining, Melbourne, Australia, June, 2018.
  4. Vamplew, P., Webb, D., Zintgraf, L.M., Roijers, D.M., Dazeley, R., Issabekov, R. and Dekker, E. (2017), MORL-Glue: A Benchmark Suite for Multi-Objective Reinforcement Learning, The 29th Benelux Conference on Artificial Intelligence, Groningen, The Netherlands.
  5. Ul Haq, I., Gondal, I. and Vamplew, P. (2016) Generating Synthetic Datasets for Experimental Validation of Fraud Detection, Fourteenth Australasian Data Mining Conference, Canberra, Australia.
  6. Vamplew, P., Issabekov, R., Dazeley, R. and Foale, C. (2015), Reinforcement Learning of Pareto-Optimal Policies Using Steering, Australasian Joint Conference on Artificial Intelligence, Canberra, December 2015, Lecture Notes in Computer Science, Vol 9457, pp 596-608.
  7. Achterbosch, L., Miller, C. and Vamplew, P. (2013), Ganking, Corpse Camping and Ninja Looting from the perception of the MMORPG community: Acceptable Behavior or Unacceptable Griefing?, 9th Australasian Conference on Interactive Entertainment, Melbourne, September 2013.
  8. Issabekov, R. and Vamplew, P. (2012), An Empirical Comparison of Two Common Multiobjective Reinforcement Learning Algorithms, Proceedings of the Australasian  Joint Conference on Artificial Intelligence
  9. Nankervis, S., Meredith, G., Fotinatos, N., & Vamplew, P. (2012). Taming the Devil: A Game-Based Approach to Teaching Immunology. Proceedings of the Australian Society for Computers in Learning in Tertiary Education conference. Wellington, New Zealand.
  10. Maruatona, O., Vamplew, P. and Dazeley, R. (2012), Prudent Fraud Detection in Internet Banking, Proceedings of the Workshop on Cybercrime and Trusted Computing
  11. Sukhorukova, N., Stranieri, A., Ofoghi, B., Vamplew, P., Saleem, M., Ma, L.,  Ugon, A., Ugon, J.,  Muecke, N., Amiel, H., Philippe, C., Bani-Mustafa, A., Huda, S., Bertoli, M., Lévy, P., Ganascia, J-G (2010), Automatic sleep stage identification: difficulties and possible solutions, Proceedings of the Australian Computer Science Conference, January 2010, Gold Coast, Australia.
  12. Yearwood, J., Webb, D., Vamplew, P., Ma, L.  Ofoghi, B. and Kelarev, A. (2009), Applying Clustering and Ensemble Clustering Approaches to Phishing Profiling, The Australasian Data Mining Conference: AusDM 2009, Melbourne, Australia, December 2009.
  13. Vamplew, P., Dazeley, R., Barker, E. and Kelarev, A. (2009), Constructing Stochastic Mixture Policies for Episodic Multiobjective Reinforcement Learning Tasks, Proceedings of AI09: The 22nd Australasian Conference on Artificial Intelligence, Melbourne, Australia, December 2009, Springer, Lecture Notes in Artificial Intelligence Vol 5866.
  14. Zarnegar, A., Vamplew, P. and Stranieri, A. (2009) Inference of Gene Expression Networks Using Memetic Gene Expression Programming, 32nd Aust. Computer Science Conference (ACSC), ACSW 2009, Auckland, New Zealand, 19-23 Jan 2009, CRPIT Vol.91, pp.29-35
  15. Vamplew, P., Yearwood, J., Dazeley, R. and Berry, A., (2008), On the Limitations of Scalarisation for Multiobjective Learning of Pareto Fronts, in Wobcke, W and Zhang, M (Eds), Proceedings of AI08: The 21st Australasian Conference on Artificial Intelligence, Auckland, New Zealand, December 2008, Springer, Lecture Notes in Artificial Intelligence, Vol 5360, ISBN 978-3-540-89377-6, pp 372-378
  16. Layton, R., Vamplew, P., and Turville, C., (2008), Using Stereotypes to Improve Early-Match Poker Play, in Wobcke, W and Zhang, M (Eds), Proceedings of AI08: The 21st Australasian Conference on Artificial Intelligence, Auckland, New Zealand, December 2008, Springer, Lecture Notes in Artificial Intelligence, Vol 5360, ISBN 978-3-540-89377-6, pp 584-593
  17. Foale, C. and Vamplew, P. (2007), "Portal-based Sound Propagation for First-Person Computer Games" in Proceedings of the Fourth Australian Conference on Interactive Entertainment (IE2007), ISBN: 978-1-921166-87-7
  18. Osman, D., Yearwood, J. and Vamplew, P. (2007), "Using Corpus Analysis to Inform Research into Opinion Detection in Blogs", Proceedings of the 6th Australasian Data Mining Conference, Gold Coast, December 2007, CRPIT Volume 70, ISBN978-1-920682-51-4, pp 65-75
  19. Vamplew, P., Ollington, R. and Hepburn, M. (2006), Enhanced Temporal Difference Learning Using Compiled Eligibility Traces, in Sattar, A and Kang, B-H (Eds), Proceedings of AI06: The 19th Australian Conference on Artificial Intelligence, Hobart, Tasmania, 3-5 December 2006., Springer, Lecture Notes in Artificial Intelligence, Vol 4304, ISBN 978-3-540-49787-5, pp 141-150
  20. Vamplew, P and Ollington, R (2005) "Global Versus Local Constructive Function Approximation for On-Line Reinforcement Learning", in Zhang, Shichao; Jarvis, Ray (Eds.) 18th Australian Joint Conference on Artificial Intelligence, Sydney, Australia, December 5-9, 2005, Springer, Lecture Notes in Artificial Intelligence, Vol.3809 ISBN: 3-540-30462-2, pp 113-122
  21. Temby, L, Vamplew, P and Berry, A (2005), "Accelerating Real-Valued Genetic Algorithms Using Mutation-With-Momentum", at AI'05: The 18th Australian Joint Conference on Artificial Intelligence, Sydney, Australia, December 2005, in Zhang, Shichao; Jarvis, Ray (Eds.) 18th Australian Joint Conference on Artificial Intelligence, Sydney, Australia, December 5-9, 2005, Springer, Lecture Notes in Artificial Intelligence, Vol.3809 ISBN: 3-540-30462-2, pp 1108-1111
  22. Vamplew, P.W. and Dermoudy, J. (2005), "An Anti-Plagiarism Editor for Software Development Courses", in Alison Young, Denise Tolhurst (Eds.): Seventh Australasian Computing Education Conference (ACE 2005), Newcastle, NSW, Australia, January/February 2005. CRPIT 42 Australian Computer Society 2005, ISBN 1-920682-24-4, pp 83-90
  23. Vamplew, P., Clark, D., Adams, A and Muench, J. (1996), "Techniques for Dealing with Missing Values in Feedforward Networks", in ACNN'96: Proceedings of the Seventh Australian Conference on Neural Networks, Canberra, 1996
  24. Vamplew, P and Adams, A (1994), "Neural Transplant Surgery: An Approach to Pre-training Recurrent Networks" in Tsio, A.C. and Downs, T. (eds), Proceedings of the Fifth Australian Conference on Neural Networks, University of Queensland, February 1994, pp 105-108
  25. Vamplew, P (1993), "The SLARTI Sign Language Recognition System: A Progress Report" at the Australian Conference on Technology and People With Disabilities, Regency Park Centre for the Young Disabled, Adelaide, 5-7 July 1993, pp 46-48.
  26. Bye, S, Adams, A and Vamplew, P (1993), "The Self-Growing Feed-Forward Counterpropagation Network" at ACNN'93: The Fourth Australian Conference on Neural Networks, University of Melbourne, 1-3 February 1993
  27. Vamplew, P and Adams, A (1992), "Missing Values in a Backpropagation Neural Net" at Leong, P and Jabri, M (eds), ACNN'92: The Third Australian Conference on Neural Networks, Sydney University1992, pp 64-67
  28. Adams, A, Bye, S, and Vamplew, P (1991) "A New Activation Function for the Backpropagation Neural Network" in Maeder, A. J. and Jenkins, B.M., (eds), Proceedings of   DICTA-91 Digital Image Computing: Techniques and Applications, Melbourne, 4-6 December, Australian Pattern Recognition Society, 1991, ISBN 0-646-07338-9, pp 132-137
  29. Vamplew, P (1991), "Computer Recognition of Sign Language" in Thorne, J.G. (ed)., Paper Clips to Silicon Chips: Second National Conference on Disability Issues and Technology, Hobart, 6-9 October 1991

Theses

  1. Vamplew, P, "Recognition of Sign Language Using Neural Networks", PhD Thesis, Department of Computer Science, University of Tasmania, May 1996

Editorial publications

  1. Drugan, M., Wiering, M., Vamplew, P. and Chetty, M. (eds.), (2017), Multiobjective Reinforcement Learning: Theory and Applications, Special Issue of Neurocomputing Journal, Vol 263.
  2. Vamplew, P., Stranieri, A., Ong, K-L., Christen, P. and Kennedy, P. (eds.) (2011), Proceedings of the Ninth Australasian Data Mining Conference (AusDM2011), Conferences in Research and Practice in Information Technology (CRPIT), Vol. 121.
  3. Vamplew, P (ed) (1992), "AI'92: Summary of the IR&DB Technology Transfer Session of the 5th Australian Joint Conference on Artificial Intelligence", 16-18 November 1992, Hobart, Tasmania

Unrefereed publications

  1. Vamplew, P. (2014), How to get published without writing anything (except a cheque), Campus Review, December 2014, p15.
  2. Miner, A., Vamplew, P., Windle, D. J., Flentje, P., & Warner, P. (2010). A comparative study of various data mining techniques as applied to the modeling of landslide susceptibility on the Bellarine Peninsula, Victoria, Australia, In A. L. Williams, G. M. Pinches, C. Y. Chin, T. J. McMorran & C. I. Massey (Eds.), International Congress of the International Association of Engineering Geology and the Environment (pp. 1-9). Boca Raton, FL, USA: CRC Press.
  3. Graymore, M., Block, J., Wallis, A., Vamplew, P., McRae-Williams, P., Mitchell, B.and O'Toole, K. (2010), WINDSCREEN: A climate change visualisation tool for water allocation decisions, 2010 International Climate Change Adaptation Conference, 29 June - 1 July 2010, Gold Coast, Queensland.
  4. McRae-Williams, P., Mitchell, B., Block, J., Wallis, A., Vamplew, P., Graymore, M. and K., O. T. (2009). Driving Water Futures: The Use of an Interactive Visualisation Tool for Community Water Allocation Engagement, Report # 03/09, Water in Drylands Collaborative Research Program, University of Ballarat.
  5. Graymore, M., P. McRae-Williams, J. Block, B. Mitchell, A. Wallis, K. O'Toole and P. Vamplew (2009), "Footy, Flows and Farms: A Visualisation Tool for Determining Community Water Allocation Preferences", 21st Conference for the Pacific Regional Science Conference Organisation, Gold Coast, July 19 - 22, 2009
  6. Vamplew, P and Adams, A (1992), "The SLARTI System: Computer sign language recognition" in AASE National Newsletter, Australian Association of Special Education, No2, p 9 (article requested by the editor)
  7. Bye, S, Adams, A and Vamplew, P (1992), "A Self-Growing Neural Architecture for Classification", Technical report R92-3, Department of Computer Science, University of Tasmania, Hobart.
  8. Vamplew, P and Adams, A (1991), "Real World Problems in Backpropagation", Technical Report R91-4, Department of Computer Science, University of Tasmania, Hobart, December.

Research interests

  • Multiobjective reinforcement learning
  • Explainable artificial intelligence (XAI)
  • AI safety

Any other information

I am an Associate Editor for Neurocomputing journal, and a grant reviewer for the Australia Research Council, the Flanders Research Foundation (FWO) and the Dutch Research Council (NOW).