Peter Vamplew

Publication Activity (10 Years)

Years Active: 1995-2024
Publications (10 Years): 64

Top Topics

Reinforcement Learning

Fraud Detection

Top Venues

Neural Comput. Appl.

Comput. Games J.

Publications

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
Utility-Based Reinforcement Learning: Unifying Single-objective and Multi-objective Reinforcement Learning. CoRR (2024)
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
Utility-Based Reinforcement Learning: Unifying Single-objective and Multi-objective Reinforcement Learning. AAMAS (2024)
Peter Vamplew, Cameron Foale, Richard Dazeley
Value function interference and greedy action selection in value-based multi-objective reinforcement learning. CoRR (2024)
Adrian Ly, Richard Dazeley, Peter Vamplew, Francisco Cruz, Sunil Aryal
Elastic step DQN: A novel multi-step algorithm to alleviate overestimation in Deep Q-Networks. Neurocomputing 576 (2024)
Kewen Ding, Peter Vamplew, Cameron Foale, Richard Dazeley
An Empirical Investigation of Value-Based Multi-objective Reinforcement Learning for Stochastic Environments. CoRR (2024)
Leigh Achterbosch, Peter Vamplew, Evita March
Assessing the impact of griefing in MMORPGs using self-determination theory. Comput. Hum. Behav. 161 (2024)
Adam Bignold, Francisco Cruz, Richard Dazeley, Peter Vamplew, Cameron Foale
Human engagement providing evaluative and informative advice for interactive reinforcement learning. Neural Comput. Appl. 35 (25) (2023)
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
A Brief Guide to Multi-Objective Reinforcement Learning and Planning. AAMAS (2023)
Francisco Cruz, Richard Dazeley, Peter Vamplew, Ithan Moreira
Explainable robotic systems: understanding goal-driven actions in a reinforcement learning scenario. Neural Comput. Appl. 35 (25) (2023)
Adam Bignold, Francisco Cruz, Matthew E. Taylor, Tim Brys, Richard Dazeley, Peter Vamplew, Cameron Foale
A conceptual framework for externally-influenced agents: an assisted reinforcement learning review. J. Ambient Intell. Humaniz. Comput. 14 (4) (2023)
Adam Bignold, Francisco Cruz, Richard Dazeley, Peter Vamplew, Cameron Foale
Persistent rule-based interactive reinforcement learning. Neural Comput. Appl. 35 (32) (2023)
Hadassah Harland, Richard Dazeley, Bahareh Nakisa, Francisco Cruz, Peter Vamplew
AI apology: interactive multi-objective reinforcement learning for human-aligned AI. Neural Comput. Appl. 35 (23) (2023)
Catalin Mitelut, Ben Smith, Peter Vamplew
Intent-aligned AI systems deplete human agency: the need for agency foundations research in AI safety. CoRR (2023)
Richard Dazeley, Peter Vamplew, Francisco Cruz
Explainable reinforcement learning for broad-XAI: a conceptual framework and survey. Neural Comput. Appl. 35 (23) (2023)
Adrian Ly, Richard Dazeley, Peter Vamplew, Francisco Cruz, Sunil Aryal
Elastic step DDPG: Multi-step reinforcement learning for improved sample efficiency. IJCNN (2023)
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
Scalar Reward is Not Enough. AAMAS (2023)
Francisco Cruz, Adam Bignold, Hung Son Nguyen, Richard Dazeley, Peter Vamplew
Broad-persistent Advice for Interactive Reinforcement Learning Scenarios. CoRR (2022)
Adrian Ly, Richard Dazeley, Peter Vamplew, Francisco Cruz, Sunil Aryal
Elastic Step DQN: A novel multi-step algorithm to alleviate overestimation in Deep QNetworks. CoRR (2022)
Francisco Cruz, Charlotte Young, Richard Dazeley, Peter Vamplew
Evaluating Human-like Explanations for Robot Actions in Reinforcement Learning Scenarios. IROS (2022)
Francisco Cruz, Charlotte Young, Richard Dazeley, Peter Vamplew
Evaluating Human-like Explanations for Robot Actions in Reinforcement Learning Scenarios. CoRR (2022)
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
Scalar reward is not enough: a response to Silver, Singh, Precup and Sutton (2021). Auton. Agents Multi Agent Syst. 36 (2) (2022)
Budi Kurniawan, Peter Vamplew, Michael Papasimeon, Richard Dazeley, Cameron Foale
Discrete-to-deep reinforcement learning methods. Neural Comput. Appl. 34 (3) (2022)
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
A practical guide to multi-objective reinforcement learning and planning. Auton. Agents Multi Agent Syst. 36 (1) (2022)
Mohammad Mirzanejad, Morteza Ebrahimi, Peter Vamplew, Hadi Veisi
An online scalarization multi-objective reinforcement learning algorithm: TOPSIS Q-learning. Knowl. Eng. Rev. 37 (2022)
Peter Vamplew, Cameron Foale, Richard Dazeley
The impact of environmental stochasticity on value-based multiobjective reinforcement learning. Neural Comput. Appl. 34 (3) (2022)
Richard Dazeley, Peter Vamplew, Cameron Foale, Charlotte Young, Sunil Aryal, Francisco Cruz
Levels of explainable artificial intelligence for human-aligned conversational explanations. Artif. Intell. 299 (2021)
Richard Dazeley, Peter Vamplew, Cameron Foale, Charlotte Young, Sunil Aryal, Francisco Cruz
Levels of explainable artificial intelligence for human-aligned conversational explanations. CoRR (2021)
Peter Vamplew, Cameron Foale, Richard Dazeley, Adam Bignold
Potential-based multiobjective reinforcement learning approaches to low-impact agents for AI safety. Eng. Appl. Artif. Intell. 100 (2021)
Adam Bignold, Francisco Cruz, Richard Dazeley, Peter Vamplew, Cameron Foale
Persistent Rule-based Interactive Reinforcement Learning. CoRR (2021)
Richard Dazeley, Peter Vamplew, Francisco Cruz
Explainable Reinforcement Learning for Broad-XAI: A Conceptual Framework and Survey. CoRR (2021)
Ngoc Duy Nguyen, Thanh Thi Nguyen, Peter Vamplew, Richard Dazeley, Saeid Nahavandi
A Prioritized objective actor-critic method for deep reinforcement learning. Neural Comput. Appl. 33 (16) (2021)
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
A Practical Guide to Multi-Objective Reinforcement Learning and Planning. CoRR (2021)
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
Scalar reward is not enough: A response to Silver, Singh, Precup and Sutton (2021). CoRR (2021)
Goodger Nikolaj, Peter Vamplew, Cameron Foale, Richard Dazeley
Language Representations for Generalization in Reinforcement Learning. ACML (2021)
Budi Kurniawan, Peter Vamplew, Michael Papasimeon, Richard Dazeley, Cameron Foale
Discrete-to-Deep Supervised Policy Learning. CoRR (2020)
Paul Black, Ammar Sohail, Iqbal Gondal, Joarder Kamruzzaman, Peter Vamplew, Paul A. Watters
API Based Discrimination of Ransomware and Benign Cryptographic Programs. ICONIP (2) (2020)
Adam Bignold, Francisco Cruz, Matthew E. Taylor, Tim Brys, Richard Dazeley, Peter Vamplew, Cameron Foale
A Conceptual Framework for Externally-influenced Agents: An Assisted Reinforcement Learning Review. CoRR (2020)
Jordan Greenwood, Leigh Achterbosch, Grant Meredith, Peter Vamplew
Motivational Factors of Australian Mobile Gamers. ACSW (2020)
Ikram Ul Haq, Iqbal Gondal, Peter Vamplew
Unified Expression Ripple Down Rules based Fraud Detection Technique for Scalable Data. ICDM (2020)
Adam Bignold, Francisco Cruz, Richard Dazeley, Peter Vamplew, Cameron Foale
Human Engagement Providing Evaluative and Informative Advice for Interactive Reinforcement Learning. CoRR (2020)
Paul Black, Iqbal Gondal, Peter Vamplew, Arun Lakhotia
Identifying Cross-Version Function Similarity Using Contextual Features. TrustCom (2020)
Thanh Thi Nguyen, Ngoc Duy Nguyen, Peter Vamplew, Saeid Nahavandi, Richard Dazeley, Chee Peng Lim
A multi-objective deep reinforcement learning framework. Eng. Appl. Artif. Intell. 96 (2020)
Francisco Cruz, Richard Dazeley, Peter Vamplew
Explainable robotic systems: Interpreting outcome-focused actions in a reinforcement learning scenario. CoRR (2020)
Peter Vamplew, Cameron Foale, Richard Dazeley
A Demonstration of Issues with Value-Based Multiobjective Reinforcement Learning Under Stochastic State Transitions. CoRR (2020)
Armita Zarnegar, Herbert F. Jelinek, Peter Vamplew, Andrew Stranieri
Integrating Biological Heuristics and Gene Expression Data for Gene Regulatory Network Inference. ACSW (2019)
Paul Black, Iqbal Gondal, Peter Vamplew, Arun Lakhotia
Evolved Similarity Techniques in Malware Analysis. TrustCom/BigDataSE (2019)
Ansam Khraisat, Iqbal Gondal, Peter Vamplew, Joarder Kamruzzaman
Survey of intrusion detection systems: techniques, datasets and challenges. Cybersecur. 2 (1) (2019)
Francisco Cruz, Richard Dazeley, Peter Vamplew
Memory-Based Explainable Reinforcement Learning. Australasian Conference on Artificial Intelligence (2019)
Ikram Ul Haq, Iqbal Gondal, Peter Vamplew
Enhancing Model Performance for Fraud Detection by Feature Engineering and Compact Unified Expressions. ICA3PP (2) (2019)
Budi Kurniawan, Peter Vamplew, Michael Papasimeon, Richard Dazeley, Cameron Foale
An Empirical Study of Reward Structures for Actor-Critic Reinforcement Learning in Air Combat Manoeuvring Simulation. Australasian Conference on Artificial Intelligence (2019)
Leigh Achterbosch, Charlynn Miller, Christopher Turville, Peter Vamplew
Correction to: Griefers Versus the Griefed - What Motivates Them to Play Massively Multiplayer Online Role-Playing Games? Comput. Games J. 7 (1) (2018)
Alastair Lansley, Peter Vamplew, Cameron Foale, Philip Smith
SoniFight: Software to Provide Additional Sonification Cues to Video Games for Visually Impaired Players. Comput. Games J. 7 (2) (2018)
Ikram Ul Haq, Iqbal Gondal, Peter Vamplew, Simon Brown
Categorical Features Transformation with Compact One-Hot Encoder for Fraud Detection in Distributed Environment. AusDM (2018)
Peter Vamplew, Richard Dazeley, Cameron Foale, Tanveer A. Choudhury
Non-functional regression: A new challenge for neural networks. Neurocomputing 314 (2018)
Omaru Maruatona, Peter Vamplew, Richard Dazeley, Paul A. Watters
Rapid Anomaly Detection Using Integrated Prudence Analysis (IPA). PAKDD (Workshops) (2018)
Ansam Khraisat, Iqbal Gondal, Peter Vamplew
An Anomaly Intrusion Detection System Using C5 Decision Tree Classifier. PAKDD (Workshops) (2018)
Peter Vamplew, Richard Dazeley, Cameron Foale, Sally Firmin, Jane Mummery
Human-aligned artificial intelligence is a multiobjective problem. Ethics Inf. Technol. 20 (1) (2018)
Vishakha Sharma, Andrew Stranieri, Julien Ugon, Peter Vamplew, Laura Martin
An Agile Group Aware Process beyond CRISP-DM: A Hospital Data Mining Case Study. ICCDA (2017)
Peter Vamplew, Richard Dazeley, Cameron Foale
Softmax exploration strategies for multiobjective reinforcement learning. Neurocomputing 263 (2017)
Leigh Achterbosch, Charlynn Miller, Peter Vamplew
A taxonomy of griefer type by motivation in massively multiplayer online role-playing games. Behav. Inf. Technol. 36 (8) (2017)
Peter Vamplew, Rustam Issabekov, Richard Dazeley, Cameron Foale, Adam Berry, Tim Moore, Douglas C. Creighton
Steering approaches to Pareto-optimal multiobjective reinforcement learning. Neurocomputing 263 (2017)
Omaru Maruatona, Peter Vamplew, Richard Dazeley, Paul A. Watters
Evaluating Accuracy in Prudence Analysis for Cyber Security. ICONIP (5) (2017)
Madalina M. Drugan, Marco A. Wiering, Peter Vamplew, Madhu Chetty
Special issue on multi-objective reinforcement learning. Neurocomputing 263 (2017)
Armita Zarnegar, Peter Vamplew, Andrew Stranieri, Herbert F. Jelinek
A Heuristic Gene Regulatory Networks Model for Cardiac Function and Pathology. CinC (2016)
Peter Vamplew, Rustam Issabekov, Richard Dazeley, Cameron Foale
Reinforcement Learning of Pareto-Optimal Multiobjective Policies Using Steering. Australasian Conference on Artificial Intelligence (2015)
Jin Wang, Chee Peng Lim, Douglas C. Creighton, Abbas Khosravi, Saeid Nahavandi, Julien Ugon, Peter Vamplew, Andrew Stranieri, Laura Martin, Anton Freischmidt
Patient admission prediction using a pruned fuzzy min-max neural network with rule extraction. Neural Comput. Appl. 26 (2) (2015)
Leigh Achterbosch, Charlynn Miller, Christopher Turville, Peter Vamplew
Griefers versus the Griefed - what motivates them to play Massively Multiplayer Online Role-Playing Games? Comput. Games J. 3 (1) (2014)
Diederik Marijn Roijers, Peter Vamplew, Shimon Whiteson, Richard Dazeley
A Survey of Multi-Objective Sequential Decision-Making. CoRR (2014)
Diederik M. Roijers, Peter Vamplew, Shimon Whiteson, Richard Dazeley
A Survey of Multi-Objective Sequential Decision-Making. J. Artif. Intell. Res. 48 (2013)
Leigh Achterbosch, Charlynn Miller, Peter Vamplew
Ganking, corpse camping and ninja looting from the perception of the MMORPG community: acceptable behavior or unacceptable griefing? IE (2013)
Omaru Maruatona, Peter Vamplew, Richard Dazeley
RM and RDM, a Preliminary Evaluation of Two Prudent RDR Techniques. PKAW (2012)
Rosemary Torney, Peter Vamplew, John Yearwood
Using psycholinguistic features for profiling first language of authors. J. Assoc. Inf. Sci. Technol. 63 (6) (2012)
Rustam Issabekov, Peter Vamplew
An Empirical Comparison of Two Common Multiobjective Reinforcement Learning Algorithms. Australasian Conference on Artificial Intelligence (2012)
Peter Vamplew, Richard Dazeley, Adam Berry, Rustam Issabekov, Evan Dekker
Empirical evaluation methods for multiobjective reinforcement learning algorithms. Mach. Learn. 84 (1-2) (2011)
Subhasis Mukherjee, John Yearwood, Peter Vamplew, Md. Shamsul Huda
Reinforcement Learning Approach to AIBO Robot's Decision Making Process in Robosoccer's Goal Keeper Problem. SNPD (2011)
Deanna J. Osman, John Yearwood, Peter Vamplew
Automated opinion detection: Implications of the level of agreement between human raters. Inf. Process. Manag. 46 (3) (2010)
Richard Dazeley, Philip Warner, Scott Johnson, Peter Vamplew
The Ballarat Incremental Knowledge Engine. PKAW (2010)
Armita Zarnegar, Peter Vamplew, Andrew Stranieri
Inference of Gene Expression Networks Using Memetic Gene Expression Programming. ACSC (2009)
Peter Vamplew, Richard Dazeley, Ewan Barker, Andrei V. Kelarev
Constructing Stochastic Mixture Policies for Episodic Multiobjective Reinforcement Learning Tasks. Australasian Conference on Artificial Intelligence (2009)
Deanna J. Osman, John Yearwood, Peter Vamplew
Weblogs for market research: finding more relevant opinion documents using system fusion. Online Inf. Rev. 33 (5) (2009)
John Yearwood, Dean Webb, Liping Ma, Peter Vamplew, Bahadorreza Ofoghi, Andrei V. Kelarev
Applying Clustering and Ensemble Clustering Approaches to phishing Profiling. AusDM (2009)
Mofakharul Islam, Peter Vamplew, John Yearwood
MRF Model Based Unsupervised Color Textured Image Segmentation Using Multidimensional Spatially Variant Finite Mixture Model. EIAT/IETA (2008)
Mofakharul Islam, John Yearwood, Peter Vamplew
Unsupervised Segmentation of Industrial Images Using Markov Random Field Model. EIAT/IETA (2008)
Peter Vamplew, John Yearwood, Richard Dazeley, Adam Berry
On the Limitations of Scalarisation for Multi-objective Reinforcement Learning of Pareto Fronts. Australasian Conference on Artificial Intelligence (2008)
Robert Layton, Peter Vamplew, Chris Turville
Using Stereotypes to Improve Early-Match Poker Play. Australasian Conference on Artificial Intelligence (2008)
Cameron Foale, Peter Vamplew
Portal-based sound propagation for first-person computer games. IE (2007)
Mofakharul Islam, John Yearwood, Peter Vamplew
Unsupervised Color Textured Image Segmentation Using Cluster Ensembles and MRF Model. SCSS (1) (2007)
Deanna J. Osman, John Yearwood, Peter Vamplew
Using Corpus Analysis to Inform Research into Opinion Detection in Blogs. AusDM (2007)
David Johnson, Vishv M. Malhotra, Peter Vamplew
More Effective Web Search Using Bigrams and Trigrams. Webology 3 (4) (2006)
Adam Berry, Peter Vamplew
An efficient approach to unbounded bi-objective archives -: introducing the mak_tree algorithm. GECCO (2006)
Peter Vamplew, Robert Ollington, Mark Hepburn
Enhanced Temporal Difference Learning Using Compiled Eligibility Traces. Australian Conference on Artificial Intelligence (2006)
Peter Vamplew, Julian R. Dermoudy
An Anti-Plagiarism Editor for Software Development Courses. ACE (2005)
Robert Ollington, Peter Vamplew
Concurrent Q-learning: Reinforcement learning for dynamic goals and environments. Int. J. Intell. Syst. 20 (10) (2005)
Luke Temby, Peter Vamplew, Adam Berry
Accelerating Real-Valued Genetic Algorithms Using Mutation-with-Momentum. Australian Conference on Artificial Intelligence (2005)
Peter Vamplew, Robert Ollington
On-Line Reinforcement Learning Using Cascade Constructive Neural Networks. KES (3) (2005)
Peter Vamplew, Robert Ollington
Global Versus Local Constructive Function Approximation for On-Line Reinforcement Learning. Australian Conference on Artificial Intelligence (2005)
Adam Berry, Peter Vamplew
The Combative Accretion Model - Multiobjective Optimisation Without Explicit Pareto Ranking. EMO (2005)
Adam Berry, Peter Vamplew
A simplified artificial life model for multiobjective optimisation: a preliminary report. IEEE Congress on Evolutionary Computation (2003)
Peter Vamplew, Anthony Adams
Recognition and anticipation of hand motions using a recurrent neural network. ICNN (1995)