Richard Dazeley

Publication Activity (10 Years)

Years Active: 2003-2024
Publications (10 Years): 65

Top Topics

Reinforcement Learning

State Transitions

Top Venues

Neural Comput. Appl.

Australasian Conference on Artificial Intelligence

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)
Sheldon Fung, Wei Pan, Xiao Liu, John Yearwood, Richard Dazeley, Xuequan Lu
TopFormer: Topology-Aware Transformer for Point Cloud Registration. CVM (1) (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)
Weijia Wang, Wei Pan, Chaofan Dai, Richard Dazeley, Lei Wei, Bernard Rolfe, Xuequan Lu
Segmentation-driven feature-preserving mesh denoising. Vis. Comput. 40 (9) (2024)
Dhiraj Neupane, Mohamed Reda Bouadjenek, Richard Dazeley, Sunil Aryal
Data-driven Machinery Fault Detection: A Comprehensive Review. CoRR (2024)
Kewen Ding, Peter Vamplew, Cameron Foale, Richard Dazeley
An Empirical Investigation of Value-Based Multi-objective Reinforcement Learning for Stochastic Environments. CoRR (2024)
Zafaryab Rasool, Sunil Aryal, Mohamed Reda Bouadjenek, Richard Dazeley
Overcoming weaknesses of density peak clustering using a data-dependent similarity measure. Pattern Recognit. 137 (2023)
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)
Weijia Wang, Xuequan Lu, Di Shao, Xiao Liu, Richard Dazeley, Antonio Robles-Kelly, Wei Pan
Weighted Point Cloud Normal Estimation. ICME (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)
Weijia Wang, Xuequan Lu, Di Shao, Xiao Liu, Richard Dazeley, Antonio Robles-Kelly, Wei Pan
Weighted Point Cloud Normal Estimation. CoRR (2023)
Supriya Roy, Bahareh Nakisa, Pubudu N. Pathirana, Richard Dazeley
A Wearable Multi-Sensor Fusion Approach for Gender Recognition based on Deep Learning. ICBRA (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)
Francisco Cruz, Thommen George Karimpanal, Miguel A. Solis, Pablo Barros, Richard Dazeley
Human-aligned reinforcement learning for autonomous agents and robots. Neural Comput. Appl. 35 (23) (2023)
Jianhua Li, Sophie McKenzie, Richard Dazeley, Frank Jiang, Keshav Sood
Current Status and Trends of Engineering Entrepreneurship Education in Australian Universities. CoRR (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)
Richard Dazeley, Peter Vamplew, Francisco Cruz
Explainable reinforcement learning for broad-XAI: a conceptual framework and survey. Neural Comput. Appl. 35 (23) (2023)
Hung Son Nguyen, Francisco Cruz, Richard Dazeley
Towards a Broad-Persistent Advising Approach for Deep Interactive Reinforcement Learning in Robotic Environments. Sensors 23 (5) (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)
Jincen Jiang, Xuequan Lu, Lizhi Zhao, Richard Dazeley, Meili Wang
Masked Autoencoders in 3D Point Cloud Representation Learning. CoRR (2022)
Francisco Cruz, Charlotte Young, Richard Dazeley, Peter Vamplew
Evaluating Human-like Explanations for Robot Actions in Reinforcement Learning Scenarios. CoRR (2022)
Thai Doan Chuong, Vicky H. Mak-Hau, John Yearwood, Richard Dazeley, M. T. Nguyen, T. Cao
Robust Pareto solutions for convex quadratic multiobjective optimization problems under data uncertainty. Ann. Oper. Res. 319 (2) (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)
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)
Cristian Millán-Arias, Bruno J. T. Fernandes, Francisco Cruz, Richard Dazeley, Sergio Fernandes
A Robust Approach for Continuous Interactive Actor-Critic Algorithms. IEEE Access 9 (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)
Sunil Aryal, K. C. Santosh, Richard Dazeley
usfAD: a robust anomaly detector based on unsupervised stochastic forest. Int. J. Mach. Learn. Cybern. 12 (4) (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)
Hung Son Nguyen, Francisco Cruz, Richard Dazeley
A Broad-persistent Advising Approach for Deep Interactive Reinforcement Learning in Robotic Environments. CoRR (2021)
Angel Ayala, Francisco Cruz, Bruno J. T. Fernandes, Richard Dazeley
Explainable Deep Reinforcement Learning Using Introspection in a Non-episodic Task. CoRR (2021)
Budi Kurniawan, Peter Vamplew, Michael Papasimeon, Richard Dazeley, Cameron Foale
Discrete-to-Deep Supervised Policy Learning. CoRR (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)
Angel Ayala, Francisco Cruz, Diego Campos, Rodrigo Rubio, Bruno J. T. Fernandes, Richard Dazeley
A Comparison of Humanoid Robot Simulators: A Quantitative Approach. ICDL-EPIROB (2020)
Ithan Moreira, Javier Rivas, Francisco Cruz, Richard Dazeley, Angel Ayala, Bruno J. T. Fernandes
Deep Reinforcement Learning with Interactive Feedback in a Human-Robot Environment. CoRR (2020)
Adam Bignold, Francisco Cruz, Richard Dazeley, Peter Vamplew, Cameron Foale
Human Engagement Providing Evaluative and Informative Advice for Interactive Reinforcement Learning. CoRR (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)
Cristian Millán-Arias, Bruno J. T. Fernandes, Francisco Cruz, Richard Dazeley, Sergio Fernandes
A Robust Approach for Continuous Interactive Reinforcement Learning. HAI (2020)
Peter Vamplew, Cameron Foale, Richard Dazeley
A Demonstration of Issues with Value-Based Multiobjective Reinforcement Learning Under Stochastic State Transitions. CoRR (2020)
Angel Ayala, Francisco Cruz, Diego Campos, Rodrigo Rubio, Bruno J. T. Fernandes, Richard Dazeley
A Comparison of Humanoid Robot Simulators: A Quantitative Approach. CoRR (2020)
Francisco Cruz, Richard Dazeley, Peter Vamplew
Memory-Based Explainable Reinforcement Learning. Australasian Conference on Artificial Intelligence (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)
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)
Peter Vamplew, Richard Dazeley, Cameron Foale, Sally Firmin, Jane Mummery
Human-aligned artificial intelligence is a multiobjective problem. Ethics Inf. Technol. 20 (1) (2018)
Peter Vamplew, Richard Dazeley, Cameron Foale
Softmax exploration strategies for multiobjective reinforcement learning. Neurocomputing 263 (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)
Robert Layton, Paul A. Watters, Richard Dazeley
Authorship analysis of aliases: Does topic influence accuracy? Nat. Lang. Eng. 21 (4) (2015)
Peter Vamplew, Rustam Issabekov, Richard Dazeley, Cameron Foale
Reinforcement Learning of Pareto-Optimal Multiobjective Policies Using Steering. Australasian Conference on Artificial Intelligence (2015)
Diederik Marijn Roijers, Peter Vamplew, Shimon Whiteson, Richard Dazeley
A Survey of Multi-Objective Sequential Decision-Making. CoRR (2014)
Robert Layton, Paul Andrew Watters, Richard Dazeley
Automated unsupervised authorship analysis using evidence accumulation clustering. Nat. Lang. Eng. 19 (1) (2013)
Diederik M. Roijers, Peter Vamplew, Shimon Whiteson, Richard Dazeley
A Survey of Multi-Objective Sequential Decision-Making. J. Artif. Intell. Res. 48 (2013)
Robert Layton, Paul A. Watters, Richard Dazeley
Local n-grams for Author Identification Notebook for PAN at CLEF 2013. CLEF (Working Notes) (2013)
Robert Layton, Paul Andrew Watters, Richard Dazeley
Evaluating authorship distance methods using the positive Silhouette coefficient. Nat. Lang. Eng. 19 (4) (2013)
Omaru Maruatona, Peter Vamplew, Richard Dazeley
RM and RDM, a Preliminary Evaluation of Two Prudent RDR Techniques. PKAW (2012)
Robert Layton, Paul A. Watters, Richard Dazeley
Unsupervised authorship analysis of phishing webpages. ISCIT (2012)
Andrei V. Kelarev, Richard Dazeley, Andrew Stranieri, John Yearwood, Herbert F. Jelinek
Detection of CAN by Ensemble Classifiers Based on Ripple Down Rules. PKAW (2012)
Robert Layton, Paul Andrew Watters, Richard Dazeley
Recentred local profiles for authorship attribution. Nat. Lang. Eng. 18 (3) (2012)
Paul Andrew Watters, Robert Layton, Richard Dazeley
How much material on BitTorrent is infringing content? A case study. Inf. Secur. Tech. Rep. 16 (2) (2011)
Ather Saeed, Andrew Stranieri, Richard Dazeley
Fault-tolerant data aggregation scheme for monitoring of critical events in grid based healthcare sensor networks. SpringSim (HPC) (2011)
Peter Vamplew, Richard Dazeley, Adam Berry, Rustam Issabekov, Evan Dekker
Empirical evaluation methods for multiobjective reinforcement learning algorithms. Mach. Learn. 84 (1-2) (2011)
Richard Dazeley, Sung Sik Park, Byeong Ho Kang
Online knowledge validation with prudence analysis in a document management application. Expert Syst. Appl. 38 (9) (2011)
Richard Dazeley, John Yearwood, Byeong Ho Kang, Andrei V. Kelarev
Consensus Clustering and Supervised Classification for Profiling Phishing Emails in Internet Commerce Security. PKAW (2010)
Richard Dazeley, Philip Warner, Scott Johnson, Peter Vamplew
The Ballarat Incremental Knowledge Engine. PKAW (2010)
Robert Layton, Paul A. Watters, Richard Dazeley
Automatically determining phishing campaigns using the USCAP methodology. eCrime (2010)
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)
Richard Dazeley, Byeong Ho Kang
Epistemological Approach to the Process of Practice. Minds Mach. 18 (4) (2008)
Richard Dazeley, Byeong Ho Kang
Generalising Symbolic Knowledge in Online Classification and Prediction. PKAW (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)
Richard Dazeley, Byeong Ho Kang
An Approach for Generalising Symbolic Knowledge. Australasian Conference on Artificial Intelligence (2008)
Richard Dazeley, Byeong Ho Kang
Detecting the Knowledge Boundary with Prudence Analysis. Australasian Conference on Artificial Intelligence (2008)
Richard Dazeley, Byeong Ho Kang
An Augmentation Hybrid System for Document Classification and Rating. PRICAI (2004)
Richard Dazeley, Byeong Ho Kang
Weighted MCRDR: Deriving Information about Relationships between Classifications in MCRDR. Australian Conference on Artificial Intelligence (2003)
Richard Dazeley, Byeong Ho Kang
Rated MCRDR: Finding non-Linear Relationships Between Classifications in MCRDR. HIS (2003)