Peter Vamplew - RankMe

113 papers A* 3A 5B 3C 6Misc 6Journal 62Unranked 26

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Learning the Value Systems of Societies with Preference-based Multi-objective Reinforcement Learning. CoRR Andrés Holgado-Sánchez, Peter Vamplew, Richard Dazeley, Sascha Ossowski, Holger Billhardt
2025	J	`jnl`	AI apology: a critical review of apology in AI systems. Artif. Intell. Rev. Hadassah Harland, Richard Dazeley, Hashini Senaratne, Peter Vamplew, Francisco Cruz, Bahareh Nakisa
2025	J	`jnl`	An empirical investigation of value-based multi-objective reinforcement learning for stochastic environments. Knowl. Eng. Rev. Kewen Ding, Peter Vamplew, Cameron Foale, Richard Dazeley
2025	J	`jnl`	ES-C51: Expected Sarsa Based C51 Distributional Reinforcement Learning Algorithm. CoRR Rijul Tandon, Peter Vamplew, Cameron Foale
2025	J	`jnl`	Ensemble Elastic DQN: A novel multi-step ensemble approach to address overestimation in deep value-based reinforcement learning. CoRR Adrian Ly, Richard Dazeley, Peter Vamplew, Francisco Cruz, Sunil Aryal
2025	A*	`conf`	On Generalization Across Environments In Multi-Objective Reinforcement Learning. ICLR Jayden Teoh, Pradeep Varakantham, Peter Vamplew
2025	J	`jnl`	On Generalization Across Environments In Multi-Objective Reinforcement Learning. CoRR Jayden Teoh, Pradeep Varakantham, Peter Vamplew
2024	J	`jnl`	AI Apology: A Critical Review of Apology in AI Systems. CoRR Hadassah Harland, Richard Dazeley, Hashini Senaratne, Peter Vamplew, Francisco Cruz, Bahareh Nakisa
2024	J	`jnl`	Adaptive Alignment: Dynamic Preference Adjustments via Multi-Objective Reinforcement Learning for Pluralistic AI. CoRR Hadassah Harland, Richard Dazeley, Peter Vamplew, Hashini Senaratne, Bahareh Nakisa, Francisco Cruz
2024	J	`jnl`	An Empirical Investigation of Value-Based Multi-objective Reinforcement Learning for Stochastic Environments. CoRR Kewen Ding, Peter Vamplew, Cameron Foale, Richard Dazeley
2024	J	`jnl`	Assessing the impact of griefing in MMORPGs using self-determination theory. Comput. Hum. Behav. Leigh Achterbosch, Peter Vamplew, Evita March
2024	J	`jnl`	Elastic step DQN: A novel multi-step algorithm to alleviate overestimation in Deep Q-Networks. Neurocomputing Adrian Ly, Richard Dazeley, Peter Vamplew, Francisco Cruz, Sunil Aryal
2024	J	`jnl`	Multi-objective Reinforcement Learning: A Tool for Pluralistic Alignment. CoRR Peter Vamplew, Conor F. Hayes, Cameron Foale, Richard Dazeley, Hadassah Harland
2024	A*	`conf`	Position: Intent-aligned AI Systems Must Optimize for Agency Preservation. ICML Catalin Mitelut, Benjamin J. Smith, Peter Vamplew
2024	A	`conf`	Utility-Based Reinforcement Learning: Unifying Single-objective and Multi-objective Reinforcement Learning. AAMAS Peter Vamplew, Cameron Foale, Conor F. Hayes, Patrick Mannion, Enda Howley, Richard Dazeley, Scott Johnson, Johan Källström, Gabriel de Oliveira Ramos, Roxana Radulescu, Willem Röpke, Diederik M. Roijers
2024	J	`jnl`	Utility-Based Reinforcement Learning: Unifying Single-objective and Multi-objective Reinforcement Learning. CoRR Peter Vamplew, Cameron Foale, Conor F. Hayes, Patrick Mannion, Enda Howley, Richard Dazeley, Scott Johnson, Johan Källström, Gabriel de Oliveira Ramos, Roxana Radulescu, Willem Röpke, Diederik M. Roijers
2024	J	`jnl`	Value function interference and greedy action selection in value-based multi-objective reinforcement learning. CoRR Peter Vamplew, Cameron Foale, Richard Dazeley
2023	A	`conf`	A Brief Guide to Multi-Objective Reinforcement Learning and Planning. AAMAS Conor F. Hayes, Roxana Radulescu, Eugenio Bargiacchi, Johan Källström, Matthew Macfarlane, Mathieu Reymond, Timothy Verstraeten, Luisa M. Zintgraf, Richard Dazeley, Fredrik Heintz, Enda Howley, Athirai A. Irissappane, Patrick Mannion, Ann Nowé, Gabriel de Oliveira Ramos, Marcello Restelli, Peter Vamplew, Diederik M. Roijers
2023	J	`jnl`	A conceptual framework for externally-influenced agents: an assisted reinforcement learning review. J. Ambient Intell. Humaniz. Comput. Adam Bignold, Francisco Cruz, Matthew E. Taylor, Tim Brys, Richard Dazeley, Peter Vamplew, Cameron Foale
2023	J	`jnl`	AI apology: interactive multi-objective reinforcement learning for human-aligned AI. Neural Comput. Appl. Hadassah Harland, Richard Dazeley, Bahareh Nakisa, Francisco Cruz, Peter Vamplew
2023	B	`conf`	Elastic step DDPG: Multi-step reinforcement learning for improved sample efficiency. IJCNN Adrian Ly, Richard Dazeley, Peter Vamplew, Francisco Cruz, Sunil Aryal
2023	J	`jnl`	Explainable reinforcement learning for broad-XAI: a conceptual framework and survey. Neural Comput. Appl. Richard Dazeley, Peter Vamplew, Francisco Cruz
2023	J	`jnl`	Explainable robotic systems: understanding goal-driven actions in a reinforcement learning scenario. Neural Comput. Appl. Francisco Cruz, Richard Dazeley, Peter Vamplew, Ithan Moreira
2023	J	`jnl`	Human engagement providing evaluative and informative advice for interactive reinforcement learning. Neural Comput. Appl. Adam Bignold, Francisco Cruz, Richard Dazeley, Peter Vamplew, Cameron Foale
2023	J	`jnl`	Intent-aligned AI systems deplete human agency: the need for agency foundations research in AI safety. CoRR Catalin Mitelut, Ben Smith, Peter Vamplew
2023	J	`jnl`	Persistent rule-based interactive reinforcement learning. Neural Comput. Appl. Adam Bignold, Francisco Cruz, Richard Dazeley, Peter Vamplew, Cameron Foale
2023	A	`conf`	Scalar Reward is Not Enough. AAMAS Peter Vamplew, Benjamin J. Smith, Johan Källström, Gabriel de Oliveira Ramos, Roxana Radulescu, Diederik M. Roijers, Conor F. Hayes, Friedrik Hentz, Patrick Mannion, Pieter J. K. Libin, Richard Dazeley, Cameron Foale
2022	J	`jnl`	A practical guide to multi-objective reinforcement learning and planning. Auton. Agents Multi Agent Syst. Conor F. Hayes, Roxana Radulescu, Eugenio Bargiacchi, Johan Källström, Matthew Macfarlane, Mathieu Reymond, Timothy Verstraeten, Luisa M. Zintgraf, Richard Dazeley, Fredrik Heintz, Enda Howley, Athirai A. Irissappane, Patrick Mannion, Ann Nowé, Gabriel de Oliveira Ramos, Marcello Restelli, Peter Vamplew, Diederik M. Roijers
2022	J	`jnl`	An online scalarization multi-objective reinforcement learning algorithm: TOPSIS Q-learning. Knowl. Eng. Rev. Mohammad Mirzanejad, Morteza Ebrahimi, Peter Vamplew, Hadi Veisi
2022	J	`jnl`	Broad-persistent Advice for Interactive Reinforcement Learning Scenarios. CoRR Francisco Cruz, Adam Bignold, Hung Son Nguyen, Richard Dazeley, Peter Vamplew
2022	J	`jnl`	Discrete-to-deep reinforcement learning methods. Neural Comput. Appl. Budi Kurniawan, Peter Vamplew, Michael Papasimeon, Richard Dazeley, Cameron Foale
2022	J	`jnl`	Elastic Step DQN: A novel multi-step algorithm to alleviate overestimation in Deep QNetworks. CoRR Adrian Ly, Richard Dazeley, Peter Vamplew, Francisco Cruz, Sunil Aryal
2022	A	`conf`	Evaluating Human-like Explanations for Robot Actions in Reinforcement Learning Scenarios. IROS Francisco Cruz, Charlotte Young, Richard Dazeley, Peter Vamplew
2022	J	`jnl`	Evaluating Human-like Explanations for Robot Actions in Reinforcement Learning Scenarios. CoRR Francisco Cruz, Charlotte Young, Richard Dazeley, Peter Vamplew
2022	J	`jnl`	Scalar reward is not enough: a response to Silver, Singh, Precup and Sutton (2021). Auton. Agents Multi Agent Syst. Peter Vamplew, Benjamin J. Smith, Johan Källström, Gabriel de Oliveira Ramos, Roxana Radulescu, Diederik M. Roijers, Conor F. Hayes, Fredrik Heintz, Patrick Mannion, Pieter J. K. Libin, Richard Dazeley, Cameron Foale
2022	J	`jnl`	The impact of environmental stochasticity on value-based multiobjective reinforcement learning. Neural Comput. Appl. Peter Vamplew, Cameron Foale, Richard Dazeley
2021	J	`jnl`	A Practical Guide to Multi-Objective Reinforcement Learning and Planning. CoRR Conor F. Hayes, Roxana Radulescu, Eugenio Bargiacchi, Johan Källström, Matthew Macfarlane, Mathieu Reymond, Timothy Verstraeten, Luisa M. Zintgraf, Richard Dazeley, Fredrik Heintz, Enda Howley, Athirai A. Irissappane, Patrick Mannion, Ann Nowé, Gabriel de Oliveira Ramos, Marcello Restelli, Peter Vamplew, Diederik M. Roijers
2021	J	`jnl`	A Prioritized objective actor-critic method for deep reinforcement learning. Neural Comput. Appl. Ngoc Duy Nguyen, Thanh Thi Nguyen, Peter Vamplew, Richard Dazeley, Saeid Nahavandi
2021	J	`jnl`	Explainable Reinforcement Learning for Broad-XAI: A Conceptual Framework and Survey. CoRR Richard Dazeley, Peter Vamplew, Francisco Cruz
2021	C	`conf`	Language Representations for Generalization in Reinforcement Learning. ACML Goodger Nikolaj, Peter Vamplew, Cameron Foale, Richard Dazeley
2021	J	`jnl`	Levels of explainable artificial intelligence for human-aligned conversational explanations. Artif. Intell. Richard Dazeley, Peter Vamplew, Cameron Foale, Charlotte Young, Sunil Aryal, Francisco Cruz
2021	J	`jnl`	Levels of explainable artificial intelligence for human-aligned conversational explanations. CoRR Richard Dazeley, Peter Vamplew, Cameron Foale, Charlotte Young, Sunil Aryal, Francisco Cruz
2021	J	`jnl`	Persistent Rule-based Interactive Reinforcement Learning. CoRR Adam Bignold, Francisco Cruz, Richard Dazeley, Peter Vamplew, Cameron Foale
2021	J	`jnl`	Potential-based multiobjective reinforcement learning approaches to low-impact agents for AI safety. Eng. Appl. Artif. Intell. Peter Vamplew, Cameron Foale, Richard Dazeley, Adam Bignold
2021	J	`jnl`	Scalar reward is not enough: A response to Silver, Singh, Precup and Sutton (2021). CoRR Peter Vamplew, Benjamin J. Smith, Johan Källström, Gabriel de Oliveira Ramos, Roxana Radulescu, Diederik M. Roijers, Conor F. Hayes, Fredrik Heintz, Patrick Mannion, Pieter J. K. Libin, Richard Dazeley, Cameron Foale
2020	J	`jnl`	A Conceptual Framework for Externally-influenced Agents: An Assisted Reinforcement Learning Review. CoRR Adam Bignold, Francisco Cruz, Matthew E. Taylor, Tim Brys, Richard Dazeley, Peter Vamplew, Cameron Foale
2020	J	`jnl`	A Demonstration of Issues with Value-Based Multiobjective Reinforcement Learning Under Stochastic State Transitions. CoRR Peter Vamplew, Cameron Foale, Richard Dazeley
2020	J	`jnl`	A multi-objective deep reinforcement learning framework. Eng. Appl. Artif. Intell. Thanh Thi Nguyen, Ngoc Duy Nguyen, Peter Vamplew, Saeid Nahavandi, Richard Dazeley, Chee Peng Lim
2020	—	`conf`	API Based Discrimination of Ransomware and Benign Cryptographic Programs. ICONIP (2) Paul Black, Ammar Sohail, Iqbal Gondal, Joarder Kamruzzaman, Peter Vamplew, Paul A. Watters
2020	J	`jnl`	Discrete-to-Deep Supervised Policy Learning. CoRR Budi Kurniawan, Peter Vamplew, Michael Papasimeon, Richard Dazeley, Cameron Foale
2020	J	`jnl`	Explainable robotic systems: Interpreting outcome-focused actions in a reinforcement learning scenario. CoRR Francisco Cruz, Richard Dazeley, Peter Vamplew
2020	J	`jnl`	Human Engagement Providing Evaluative and Informative Advice for Interactive Reinforcement Learning. CoRR Adam Bignold, Francisco Cruz, Richard Dazeley, Peter Vamplew, Cameron Foale
2020	B	`conf`	Identifying Cross-Version Function Similarity Using Contextual Features. TrustCom Paul Black, Iqbal Gondal, Peter Vamplew, Arun Lakhotia
2020	—	`conf`	Motivational Factors of Australian Mobile Gamers. ACSW Jordan Greenwood, Leigh Achterbosch, Grant Meredith, Peter Vamplew
2020	A*	`conf`	Unified Expression Ripple Down Rules based Fraud Detection Technique for Scalable Data. ICDM Ikram Ul Haq, Iqbal Gondal, Peter Vamplew
2019	—	`conf`	An Empirical Study of Reward Structures for Actor-Critic Reinforcement Learning in Air Combat Manoeuvring Simulation. Australasian Conference on Artificial Intelligence Budi Kurniawan, Peter Vamplew, Michael Papasimeon, Richard Dazeley, Cameron Foale
2019	—	`conf`	Enhancing Model Performance for Fraud Detection by Feature Engineering and Compact Unified Expressions. ICA3PP (2) Ikram Ul Haq, Iqbal Gondal, Peter Vamplew
2019	—	`conf`	Evolved Similarity Techniques in Malware Analysis. TrustCom/BigDataSE Paul Black, Iqbal Gondal, Peter Vamplew, Arun Lakhotia
2019	—	`ch.`	Griefing in MMORPGs. Encyclopedia of Computer Graphics and Games Leigh Achterbosch, Peter Vamplew
2019	—	`conf`	Integrating Biological Heuristics and Gene Expression Data for Gene Regulatory Network Inference. ACSW Armita Zarnegar, Herbert F. Jelinek, Peter Vamplew, Andrew Stranieri
2019	—	`conf`	Memory-Based Explainable Reinforcement Learning. Australasian Conference on Artificial Intelligence Francisco Cruz, Richard Dazeley, Peter Vamplew
2019	J	`jnl`	Survey of intrusion detection systems: techniques, datasets and challenges. Cybersecur. Ansam Khraisat, Iqbal Gondal, Peter Vamplew, Joarder Kamruzzaman
2018	—	`conf`	An Anomaly Intrusion Detection System Using C5 Decision Tree Classifier. PAKDD (Workshops) Ansam Khraisat, Iqbal Gondal, Peter Vamplew
2018	Misc	`conf`	Categorical Features Transformation with Compact One-Hot Encoder for Fraud Detection in Distributed Environment. AusDM Ikram Ul Haq, Iqbal Gondal, Peter Vamplew, Simon Brown
2018	J	`jnl`	Correction to: Griefers Versus the Griefed - What Motivates Them to Play Massively Multiplayer Online Role-Playing Games? Comput. Games J. Leigh Achterbosch, Charlynn Miller, Christopher Turville, Peter Vamplew
2018	J	`jnl`	Human-aligned artificial intelligence is a multiobjective problem. Ethics Inf. Technol. Peter Vamplew, Richard Dazeley, Cameron Foale, Sally Firmin, Jane Mummery
2018	J	`jnl`	Non-functional regression: A new challenge for neural networks. Neurocomputing Peter Vamplew, Richard Dazeley, Cameron Foale, Tanveer A. Choudhury
2018	—	`conf`	Rapid Anomaly Detection Using Integrated Prudence Analysis (IPA). PAKDD (Workshops) Omaru Maruatona, Peter Vamplew, Richard Dazeley, Paul A. Watters
2018	J	`jnl`	SoniFight: Software to Provide Additional Sonification Cues to Video Games for Visually Impaired Players. Comput. Games J. Alastair Lansley, Peter Vamplew, Cameron Foale, Philip Smith
2017	J	`jnl`	A taxonomy of griefer type by motivation in massively multiplayer online role-playing games. Behav. Inf. Technol. Leigh Achterbosch, Charlynn Miller, Peter Vamplew
2017	—	`conf`	An Agile Group Aware Process beyond CRISP-DM: A Hospital Data Mining Case Study. ICCDA Vishakha Sharma, Andrew Stranieri, Julien Ugon, Peter Vamplew, Laura Martin
2017	—	`conf`	Evaluating Accuracy in Prudence Analysis for Cyber Security. ICONIP (5) Omaru Maruatona, Peter Vamplew, Richard Dazeley, Paul A. Watters
2017	J	`jnl`	Softmax exploration strategies for multiobjective reinforcement learning. Neurocomputing Peter Vamplew, Richard Dazeley, Cameron Foale
2017	J	`jnl`	Special issue on multi-objective reinforcement learning. Neurocomputing Madalina M. Drugan, Marco A. Wiering, Peter Vamplew, Madhu Chetty
2017	J	`jnl`	Steering approaches to Pareto-optimal multiobjective reinforcement learning. Neurocomputing Peter Vamplew, Rustam Issabekov, Richard Dazeley, Cameron Foale, Adam Berry, Tim Moore, Douglas C. Creighton
2016	—	`conf`	A Heuristic Gene Regulatory Networks Model for Cardiac Function and Pathology. CinC Armita Zarnegar, Peter Vamplew, Andrew Stranieri, Herbert F. Jelinek
2015	J	`jnl`	Patient admission prediction using a pruned fuzzy min-max neural network with rule extraction. Neural Comput. Appl. Jin Wang, Chee Peng Lim, Douglas C. Creighton, Abbas Khosravi, Saeid Nahavandi, Julien Ugon, Peter Vamplew, Andrew Stranieri, Laura Martin, Anton Freischmidt
2015	—	`conf`	Reinforcement Learning of Pareto-Optimal Multiobjective Policies Using Steering. Australasian Conference on Artificial Intelligence Peter Vamplew, Rustam Issabekov, Richard Dazeley, Cameron Foale
2014	J	`jnl`	A Survey of Multi-Objective Sequential Decision-Making. CoRR Diederik Marijn Roijers, Peter Vamplew, Shimon Whiteson, Richard Dazeley
2014	J	`jnl`	Griefers versus the Griefed - what motivates them to play Massively Multiplayer Online Role-Playing Games? Comput. Games J. Leigh Achterbosch, Charlynn Miller, Christopher Turville, Peter Vamplew
2013	J	`jnl`	A Survey of Multi-Objective Sequential Decision-Making. J. Artif. Intell. Res. Diederik M. Roijers, Peter Vamplew, Shimon Whiteson, Richard Dazeley
2013	Misc	`conf`	Ganking, corpse camping and ninja looting from the perception of the MMORPG community: acceptable behavior or unacceptable griefing? IE Leigh Achterbosch, Charlynn Miller, Peter Vamplew
2012	—	`conf`	An Empirical Comparison of Two Common Multiobjective Reinforcement Learning Algorithms. Australasian Conference on Artificial Intelligence Rustam Issabekov, Peter Vamplew
2012	C	`conf`	RM and RDM, a Preliminary Evaluation of Two Prudent RDR Techniques. PKAW Omaru Maruatona, Peter Vamplew, Richard Dazeley
2012	J	`jnl`	Using psycholinguistic features for profiling first language of authors. J. Assoc. Inf. Sci. Technol. Rosemary Torney, Peter Vamplew, John Yearwood
2011	J	`jnl`	Empirical evaluation methods for multiobjective reinforcement learning algorithms. Mach. Learn. Peter Vamplew, Richard Dazeley, Adam Berry, Rustam Issabekov, Evan Dekker
2011	Misc	`ed.`	Ninth Australasian Data Mining Conference, AusDM 2011, Ballarat, Australia, December 2011 AusDM Peter Vamplew, Andrew Stranieri, Kok-Leong Ong, Peter Christen, Paul J. Kennedy
2011	C	`conf`	Reinforcement Learning Approach to AIBO Robot's Decision Making Process in Robosoccer's Goal Keeper Problem. SNPD Subhasis Mukherjee, John Yearwood, Peter Vamplew, Md. Shamsul Huda
2010	J	`jnl`	Automated opinion detection: Implications of the level of agreement between human raters. Inf. Process. Manag. Deanna J. Osman, John Yearwood, Peter Vamplew
2010	C	`conf`	The Ballarat Incremental Knowledge Engine. PKAW Richard Dazeley, Philip Warner, Scott Johnson, Peter Vamplew
2009	Misc	`conf`	Applying Clustering and Ensemble Clustering Approaches to phishing Profiling. AusDM John Yearwood, Dean Webb, Liping Ma, Peter Vamplew, Bahadorreza Ofoghi, Andrei V. Kelarev
2009	—	`conf`	Constructing Stochastic Mixture Policies for Episodic Multiobjective Reinforcement Learning Tasks. Australasian Conference on Artificial Intelligence Peter Vamplew, Richard Dazeley, Ewan Barker, Andrei V. Kelarev
2009	—	`ch.`	Incorporating Expert Advice into Reinforcement Learning Using Constructive Neural Networks. Constructive Neural Networks Robert Ollington, Peter Vamplew, John Swanson
2009	—	`conf`	Inference of Gene Expression Networks Using Memetic Gene Expression Programming. ACSC Armita Zarnegar, Peter Vamplew, Andrew Stranieri
2009	J	`jnl`	Weblogs for market research: finding more relevant opinion documents using system fusion. Online Inf. Rev. Deanna J. Osman, John Yearwood, Peter Vamplew
2008	—	`conf`	MRF Model Based Unsupervised Color Textured Image Segmentation Using Multidimensional Spatially Variant Finite Mixture Model. EIAT/IETA Mofakharul Islam, Peter Vamplew, John Yearwood
2008	—	`conf`	On the Limitations of Scalarisation for Multi-objective Reinforcement Learning of Pareto Fronts. Australasian Conference on Artificial Intelligence Peter Vamplew, John Yearwood, Richard Dazeley, Adam Berry
2008	—	`conf`	Unsupervised Segmentation of Industrial Images Using Markov Random Field Model. EIAT/IETA Mofakharul Islam, John Yearwood, Peter Vamplew
2008	—	`conf`	Using Stereotypes to Improve Early-Match Poker Play. Australasian Conference on Artificial Intelligence Robert Layton, Peter Vamplew, Chris Turville
2007	Misc	`conf`	Portal-based sound propagation for first-person computer games. IE Cameron Foale, Peter Vamplew
2007	—	`conf`	Unsupervised Color Textured Image Segmentation Using Cluster Ensembles and MRF Model. SCSS (1) Mofakharul Islam, John Yearwood, Peter Vamplew
2007	Misc	`conf`	Using Corpus Analysis to Inform Research into Opinion Detection in Blogs. AusDM Deanna J. Osman, John Yearwood, Peter Vamplew
2006	A	`conf`	An efficient approach to unbounded bi-objective archives -: introducing the mak_tree algorithm. GECCO Adam Berry, Peter Vamplew
2006	—	`conf`	Enhanced Temporal Difference Learning Using Compiled Eligibility Traces. Australian Conference on Artificial Intelligence Peter Vamplew, Robert Ollington, Mark Hepburn
2006	J	`jnl`	More Effective Web Search Using Bigrams and Trigrams. Webology David Johnson, Vishv M. Malhotra, Peter Vamplew
2005	—	`conf`	Accelerating Real-Valued Genetic Algorithms Using Mutation-with-Momentum. Australian Conference on Artificial Intelligence Luke Temby, Peter Vamplew, Adam Berry
2005	C	`conf`	An Anti-Plagiarism Editor for Software Development Courses. ACE Peter Vamplew, Julian R. Dermoudy
2005	J	`jnl`	Concurrent Q-learning: Reinforcement learning for dynamic goals and environments. Int. J. Intell. Syst. Robert Ollington, Peter Vamplew
2005	—	`conf`	Global Versus Local Constructive Function Approximation for On-Line Reinforcement Learning. Australian Conference on Artificial Intelligence Peter Vamplew, Robert Ollington
2005	—	`conf`	On-Line Reinforcement Learning Using Cascade Constructive Neural Networks. KES (3) Peter Vamplew, Robert Ollington
2005	C	`conf`	The Combative Accretion Model - Multiobjective Optimisation Without Explicit Pareto Ranking. EMO Adam Berry, Peter Vamplew
2003	B	`conf`	A simplified artificial life model for multiobjective optimisation: a preliminary report. IEEE Congress on Evolutionary Computation Adam Berry, Peter Vamplew
1995	—	`conf`	Recognition and anticipation of hand motions using a recurrent neural network. ICNN Peter Vamplew, Anthony Adams