Richard Dazeley

117 papers A* 3A 5B 3C 7Journal 82Unranked 17

Year	Rank	Type	Title / Venue / Authors
2026	A*	`conf`	DAPointMamba: Domain Adaptive Point Mamba for Point Cloud Completion. AAAI Yinghui Li, Qianyu Zhou, Di Shao, Hao Yang, Ye Zhu, Richard Dazeley, Xuequan Lu
2026	J	`jnl`	Diversity Sampling Regularization for Multi-Domain Generalization. Trans. Mach. Learn. Res. Lakpa Dorje Tamang, Mohamed Reda Bouadjenek, Sunil Aryal, Richard Dazeley
2026	J	`jnl`	Learning Rewards, Not Labels: Adversarial Inverse Reinforcement Learning for Machinery Fault Detection. CoRR Dhiraj Neupane, Richard Dazeley, Mohamed Reda Bouadjenek, Sunil Aryal
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
2026	J	`jnl`	TOTNet: Occlusion-aware temporal tracking for robust ball detection in sports videos. Comput. Vis. Image Underst. Hao Xu, Arbind Agrahari Baniya, Sam Wells, Mohamed Reda Bouadjenek, Richard Dazeley, Sunil Aryal
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`	Action Spotting and Precise Event Detection in Sports: Datasets, Methods, and Challenges. CoRR Hao Xu, Arbind Agrahari Baniya, Sam Well, Mohamed Reda Bouadjenek, Richard Dazeley, Sunil Aryal
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	A*	`conf`	DAPoinTr: Domain Adaptive Point Transformer for Point Cloud Completion. AAAI Yinghui Li, Qianyu Zhou, Jingyu Gong, Ye Zhu, Richard Dazeley, Xinkui Zhao, Xuequan Lu
2025	J	`jnl`	DAPointMamba: Domain Adaptive Point Mamba for Point Cloud Completion. CoRR Yinghui Li, Qianyu Zhou, Di Shao, Hao Yang, Ye Zhu, Richard Dazeley, Xuequan Lu
2025	J	`jnl`	Data-driven machinery fault diagnosis: A comprehensive review. Neurocomputing Dhiraj Neupane, Mohamed Reda Bouadjenek, Richard Dazeley, Sunil Aryal
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	J	`jnl`	Handling Out-of-Distribution Data: A Survey. CoRR Lakpa Dorje Tamang, Mohamed Reda Bouadjenek, Richard Dazeley, Sunil Aryal
2025	J	`jnl`	Handling Out-of-Distribution Data: A Survey. IEEE Trans. Knowl. Data Eng. Lakpa Dorje Tamang, Mohamed Reda Bouadjenek, Richard Dazeley, Sunil Aryal
2025	J	`jnl`	Improving out-of-distribution detection by enforcing confidence margin. Knowl. Inf. Syst. Lakpa Dorje Tamang, Mohamed Reda Bouadjenek, Richard Dazeley, Sunil Aryal
2025	J	`jnl`	Masked Autoencoders in 3D Point Cloud Representation Learning. IEEE Trans. Multim. Jincen Jiang, Xuequan Lu, Lizhi Zhao, Richard Dazeley, Meili Wang
2025	J	`jnl`	Multi-Scale Attention and Gated Shifting for Fine-Grained Event Spotting in Videos. CoRR Hao Xu, Arbind Agrahari Baniya, Sam Wells, Mohamed Reda Bouadjenek, Richard Dazeley, Sunil Aryal
2025	J	`jnl`	Optimizing Robotic Placement via Grasp-Dependent Feasibility Prediction. CoRR Tianyuan Liu, Richard Dazeley, Benjamin Champion, Akansel Cosgun
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`	DAPoinTr: Domain Adaptive Point Transformer for Point Cloud Completion. CoRR Yinghui Li, Qianyu Zhou, Jingyu Gong, Ye Zhu, Richard Dazeley, Xinkui Zhao, Xuequan Lu
2024	J	`jnl`	Data-driven Machinery Fault Detection: A Comprehensive Review. CoRR Dhiraj Neupane, Mohamed Reda Bouadjenek, Richard Dazeley, Sunil Aryal
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`	IReCa: Intrinsic Reward-enhanced Context-aware Reinforcement Learning for Human-AI Coordination. CoRR Xin Hao, Bahareh Nakisa, Mohammad Naim Rastgoo, Richard Dazeley
2024	A*	`conf`	Margin-Bounded Confidence Scores for Out-of-Distribution Detection. ICDM Lakpa Dorje Tamang, Mohamed Reda Bouadjenek, Richard Dazeley, Sunil Aryal
2024	J	`jnl`	Margin-bounded Confidence Scores for Out-of-Distribution Detection. CoRR Lakpa Dorje Tamang, Mohamed Reda Bouadjenek, Richard Dazeley, 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	J	`jnl`	Segmentation-driven feature-preserving mesh denoising. Vis. Comput. Weijia Wang, Wei Pan, Chaofan Dai, Richard Dazeley, Lei Wei, Bernard Rolfe, Xuequan Lu
2024	—	`conf`	TopFormer: Topology-Aware Transformer for Point Cloud Registration. CVM (1) Sheldon Fung, Wei Pan, Xiao Liu, John Yearwood, Richard Dazeley, Xuequan Lu
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	—	`conf`	A Wearable Multi-Sensor Fusion Approach for Gender Recognition based on Deep Learning. ICBRA Supriya Roy, Bahareh Nakisa, Pubudu N. Pathirana, Richard Dazeley
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	J	`jnl`	Current Status and Trends of Engineering Entrepreneurship Education in Australian Universities. CoRR Jianhua Li, Sophie McKenzie, Richard Dazeley, Frank Jiang, Keshav Sood
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`	Human-aligned reinforcement learning for autonomous agents and robots. Neural Comput. Appl. Francisco Cruz, Thommen George Karimpanal, Miguel A. Solis, Pablo Barros, Richard Dazeley
2023	J	`jnl`	Overcoming weaknesses of density peak clustering using a data-dependent similarity measure. Pattern Recognit. Zafaryab Rasool, Sunil Aryal, Mohamed Reda Bouadjenek, Richard Dazeley
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
2023	J	`jnl`	Towards a Broad-Persistent Advising Approach for Deep Interactive Reinforcement Learning in Robotic Environments. Sensors Hung Son Nguyen, Francisco Cruz, Richard Dazeley
2023	A	`conf`	Weighted Point Cloud Normal Estimation. ICME Weijia Wang, Xuequan Lu, Di Shao, Xiao Liu, Richard Dazeley, Antonio Robles-Kelly, Wei Pan
2023	J	`jnl`	Weighted Point Cloud Normal Estimation. CoRR Weijia Wang, Xuequan Lu, Di Shao, Xiao Liu, Richard Dazeley, Antonio Robles-Kelly, Wei Pan
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`	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`	Masked Autoencoders in 3D Point Cloud Representation Learning. CoRR Jincen Jiang, Xuequan Lu, Lizhi Zhao, Richard Dazeley, Meili Wang
2022	J	`jnl`	Robust Pareto solutions for convex quadratic multiobjective optimization problems under data uncertainty. Ann. Oper. Res. Thai Doan Chuong, Vicky H. Mak-Hau, John Yearwood, Richard Dazeley, M. T. Nguyen, T. Cao
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 Broad-persistent Advising Approach for Deep Interactive Reinforcement Learning in Robotic Environments. CoRR Hung Son Nguyen, Francisco Cruz, 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`	A Robust Approach for Continuous Interactive Actor-Critic Algorithms. IEEE Access Cristian Millán-Arias, Bruno J. T. Fernandes, Francisco Cruz, Richard Dazeley, Sérgio Fernandes
2021	J	`jnl`	Explainable Deep Reinforcement Learning Using Introspection in a Non-episodic Task. CoRR Angel Ayala, Francisco Cruz, Bruno J. T. Fernandes, Richard Dazeley
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
2021	J	`jnl`	usfAD: a robust anomaly detector based on unsupervised stochastic forest. Int. J. Mach. Learn. Cybern. Sunil Aryal, KC Santosh, Richard Dazeley
2020	—	`conf`	A Comparison of Humanoid Robot Simulators: A Quantitative Approach. ICDL-EPIROB Angel Ayala, Francisco Cruz, Diego Campos, Rodrigo Rubio, Bruno J. T. Fernandes, Richard Dazeley
2020	J	`jnl`	A Comparison of Humanoid Robot Simulators: A Quantitative Approach. CoRR Angel Ayala, Francisco Cruz, Diego Campos, Rodrigo Rubio, Bruno J. T. Fernandes, Richard Dazeley
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	B	`conf`	A Robust Approach for Continuous Interactive Reinforcement Learning. HAI Cristian Millán-Arias, Bruno J. T. Fernandes, Francisco Cruz, Richard Dazeley, Sérgio Fernandes
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	J	`jnl`	Deep Reinforcement Learning with Interactive Feedback in a Human-Robot Environment. CoRR Ithan Moreira, Javier Rivas, Francisco Cruz, Richard Dazeley, Angel Ayala, Bruno J. T. Fernandes
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
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`	Memory-Based Explainable Reinforcement Learning. Australasian Conference on Artificial Intelligence Francisco Cruz, Richard Dazeley, 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
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`	Steering approaches to Pareto-optimal multiobjective reinforcement learning. Neurocomputing Peter Vamplew, Rustam Issabekov, Richard Dazeley, Cameron Foale, Adam Berry, Tim Moore, Douglas C. Creighton
2015	J	`jnl`	Authorship analysis of aliases: Does topic influence accuracy? Nat. Lang. Eng. Robert Layton, Paul A. Watters, Richard Dazeley
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
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	J	`jnl`	Automated unsupervised authorship analysis using evidence accumulation clustering. Nat. Lang. Eng. Robert Layton, Paul Andrew Watters, Richard Dazeley
2013	J	`jnl`	Evaluating authorship distance methods using the positive Silhouette coefficient. Nat. Lang. Eng. Robert Layton, Paul Andrew Watters, Richard Dazeley
2013	—	`conf`	Local n-grams for Author Identification Notebook for PAN at CLEF 2013. CLEF (Working Notes) Robert Layton, Paul A. Watters, Richard Dazeley
2012	C	`conf`	Detection of CAN by Ensemble Classifiers Based on Ripple Down Rules. PKAW Andrei V. Kelarev, Richard Dazeley, Andrew Stranieri, John Yearwood, Herbert F. Jelinek
2012	C	`conf`	RM and RDM, a Preliminary Evaluation of Two Prudent RDR Techniques. PKAW Omaru Maruatona, Peter Vamplew, Richard Dazeley
2012	J	`jnl`	Recentred local profiles for authorship attribution. Nat. Lang. Eng. Robert Layton, Paul Andrew Watters, Richard Dazeley
2012	—	`conf`	Unsupervised authorship analysis of phishing webpages. ISCIT Robert Layton, Paul A. Watters, Richard Dazeley
2011	J	`jnl`	Empirical evaluation methods for multiobjective reinforcement learning algorithms. Mach. Learn. Peter Vamplew, Richard Dazeley, Adam Berry, Rustam Issabekov, Evan Dekker
2011	—	`conf`	Fault-tolerant data aggregation scheme for monitoring of critical events in grid based healthcare sensor networks. SpringSim (HPC) Ather Saeed, Andrew Stranieri, Richard Dazeley
2011	J	`jnl`	How much material on BitTorrent is infringing content? A case study. Inf. Secur. Tech. Rep. Paul Andrew Watters, Robert Layton, Richard Dazeley
2011	J	`jnl`	Online knowledge validation with prudence analysis in a document management application. Expert Syst. Appl. Richard Dazeley, Sung Sik Park, Byeong Ho Kang
2010	—	`conf`	Automatically determining phishing campaigns using the USCAP methodology. eCrime Robert Layton, Paul A. Watters, Richard Dazeley
2010	C	`conf`	Consensus Clustering and Supervised Classification for Profiling Phishing Emails in Internet Commerce Security. PKAW Richard Dazeley, John Yearwood, Byeong Ho Kang, Andrei V. Kelarev
2010	C	`conf`	The Ballarat Incremental Knowledge Engine. PKAW Richard Dazeley, Philip Warner, Scott Johnson, Peter Vamplew
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
2008	—	`conf`	An Approach for Generalising Symbolic Knowledge. Australasian Conference on Artificial Intelligence Richard Dazeley, Byeong Ho Kang
2008	—	`conf`	Detecting the Knowledge Boundary with Prudence Analysis. Australasian Conference on Artificial Intelligence Richard Dazeley, Byeong Ho Kang
2008	J	`jnl`	Epistemological Approach to the Process of Practice. Minds Mach. Richard Dazeley, Byeong Ho Kang
2008	C	`conf`	Generalising Symbolic Knowledge in Online Classification and Prediction. PKAW Richard Dazeley, Byeong Ho Kang
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
2004	B	`conf`	An Augmentation Hybrid System for Document Classification and Rating. PRICAI Richard Dazeley, Byeong Ho Kang
2003	C	`conf`	Rated MCRDR: Finding non-Linear Relationships Between Classifications in MCRDR. HIS Richard Dazeley, Byeong Ho Kang
2003	—	`conf`	Weighted MCRDR: Deriving Information about Relationships between Classifications in MCRDR. Australian Conference on Artificial Intelligence Richard Dazeley, Byeong Ho Kang