Daniel Kudenko

173 papers A* 2A 25B 6C 17Misc 5Journal 58Unranked 53

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Towards Sensitivity-Aware Language Models. CoRR Dren Fazlija, Iyiola E. Olatunji, Daniel Kudenko, Sandipan Sikdar
2026	J	`jnl`	Towards unbiased action value estimation in reinforcement learning. Neurocomputing Yuan Xue, Daniel Kudenko, Megha Khosla
2025	J	`jnl`	Adversarial Robustness of Neural Networks from the Perspective of Lipschitz Calculus: A Survey. ACM Comput. Surv. Monty-Maximilian Zühlke, Daniel Kudenko
2025	J	`jnl`	CubeletWorld: A New Abstraction for Scalable 3D Modeling. CoRR Azlaan Mustafa Samad, Hoang H. Nguyen, Lukas Berg, Henrik Müller, Yuan Xue, Daniel Kudenko, Zahra Ahmadi
2025	J	`jnl`	Graph learning-based generation of abstractions for reinforcement learning. Neural Comput. Appl. Yuan Xue, Daniel Kudenko, Megha Khosla
2025	J	`jnl`	Hybrid pathfinding optimization for the Lightning Network with Reinforcement Learning. Eng. Appl. Artif. Intell. Danila Valko, Daniel Kudenko
2025	J	`jnl`	Improving the Effectiveness of Potential-Based Reward Shaping in Reinforcement Learning. CoRR Henrik Müller, Daniel Kudenko
2025	A	`conf`	Improving the Effectiveness of Potential-based Reward Shaping in Reinforcement Learning. AAMAS Henrik Müller, Daniel Kudenko
2025	J	`jnl`	Increasing energy efficiency of bitcoin infrastructure with reinforcement learning and one-shot path planning for the lightning network. Neural Comput. Appl. Danila Valko, Daniel Kudenko
2025	J	`jnl`	SCOOTER: A Human Evaluation Framework for Unrestricted Adversarial Examples. CoRR Dren Fazlija, Monty-Maximilian Zühlke, Johanna Schrader, Arkadij Orlov, Clara Stein, Iyiola E. Olatunji, Daniel Kudenko
2025	A	`conf`	Streamlined Integration of GR(1) Synthesis and Reinforcement Learning for Optimizing Critical Cyber-Physical Systems. MODELS Eric Wete, Joel Greenyer, Tom Yaacov, Daniel Kudenko, Wolfgang Nejdl
2025	J	`jnl`	TCR: topologically consistent reweighting for XGBoost in regression tasks. Mach. Learn. Monty-Maximilian Zühlke, Daniel Kudenko
2025	J	`jnl`	Using incomplete and incorrect plans to shape reinforcement learning in long-sequence sparse-reward tasks. Neural Comput. Appl. Henrik Müller, Lukas Berg, Daniel Kudenko
2024	A	`conf`	Effectively Capturing Label Correlation for Tabular Multi-Label Classification. CIKM Sajjad Kamali Siahroudi, Zahra Ahmadi, Daniel Kudenko
2024	A	`conf`	Entity Matching Across Small Networks Using Node Attributes. ECAI Zahra Ahmadi, Zijian Zhang, Hoang H. Nguyen, Sergio Burdisso, Srikanth R. Madikeri, Petr Motlícek, Erinç Dikici, Gerhard Backfried, Marek Kovác, Kvetoslav Malý, Daniel Kudenko
2024	J	`jnl`	How Real Is Real? A Human Evaluation Framework for Unrestricted Adversarial Examples. CoRR Dren Fazlija, Arkadij Orlov, Johanna Schrader, Monty-Maximilian Zühlke, Michael Rohs, Daniel Kudenko
2024	A	`conf`	Multi-Robot Motion and Task Planning in Automotive Production Using Controller-based Safe Reinforcement Learning. AAMAS Eric Wete, Joel Greenyer, Daniel Kudenko, Wolfgang Nejdl
2024	—	`conf`	ROXSD: The ROXANNE Multimodal and Simulated Dataset for Advancing Criminal Investigations. Odyssey Petr Motlícek, Erinç Dikici, Srikanth R. Madikeri, Pradeep Rangappa, Miroslav Jánosík, Gerhard Backfried, Dorothea Thomas-Aniola, Maximilian Schürz, Johan Rohdin, Petr Schwarz, Marek Kovác, Kvetoslav Malý, Dominik Bobos, Mathias Leibiger, Costas Kalogiros, Andreas Alexopoulos, Daniel Kudenko, Zahra Ahmadi, Hoang H. Nguyen, Aravind Krishnan, Dawei Zhu, Dietrich Klakow, Maria Jofre, Francesco Calderoni, Denis Marraud, Nikolaos Koutras, Nikos Nikolau, Christiana Aposkiti, Panagiotis Douris, Konstantinos Gkountas, Eleni-Konstantina Sergidou, Wauter Bosma, Joshua Hughes, Hellenic Police Team
2024	J	`jnl`	Reducing CO2 emissions in a peer-to-peer distributed payment network: Does geography matter in the lightning network? Comput. Networks Danila Valko, Daniel Kudenko
2024	J	`jnl`	Sustainable broadcasting in Blockchain Network with Reinforcement Learning. CoRR Danila Valko, Daniel Kudenko
2023	J	`jnl`	An effective single-model learning for multi-label data. Expert Syst. Appl. Sajjad Kamali Siahroudi, Daniel Kudenko
2023	J	`jnl`	Inductive and transductive link prediction for criminal network analysis. J. Comput. Sci. Zahra Ahmadi, Hoang H. Nguyen, Zijian Zhang, Dmytro Bozhkov, Daniel Kudenko, Maria Jofre, Francesco Calderoni, Noa Cohen, Yosef Solewicz
2023	—	`conf`	Knowledge Graph Injection for Reinforcement Learning. DL4KG@ISWC Robert Wardenga, Liubov Kovriguina, Dmitrii Pliukhin, Daniil Radyush, Ivan SmoliakoV, Yuan Xue, Henrik Müller, Aleksei Pismerov, Dmitry Mouromtsev, Daniel Kudenko
2023	C	`conf`	MDE and Learning for flexible Planning and optimized Execution of Multi-Robot Choreographies. ETFA Eric Wete, Joel Greenyer, Andreas Wortmann, Daniel Kudenko, Wolfgang Nejdl
2023	—	`conf`	Partial Multi-label Learning via Constraint Clustering. ICONIP (11) Sajjad Kamali Siahroudi, Daniel Kudenko
2022	—	`conf`	A tool for the automation of efficient multi-robot choreography planning and execution. MoDELS (Companion) Eric Wete, Joel Greenyer, Daniel Kudenko, Wolfgang Nejdl, Oliver Flegel, Dennes Eisner
2022	—	`conf`	Assured Multi-agent Reinforcement Learning with Robust Agent-Interaction Adaptability. KES-IDT Joshua Riley, Radu Calinescu, Colin Paterson, Daniel Kudenko, Alec Banks
2022	J	`jnl`	Data Valuation for Offline Reinforcement Learning. CoRR Amir Abolfazli, Gregory Palmer, Daniel Kudenko
2022	C	`conf`	Imitating Playstyle with Dynamic Time Warping Imitation. FDG Mark Ferguson, Sam Devlin, Daniel Kudenko, James Alfred Walker
2021	—	`conf`	An Online Learning Algorithm for Non-stationary Imbalanced Data by Extra-Charging Minority Class. PAKDD (1) Sajjad Kamali Siahroudi, Daniel Kudenko
2021	—	`conf`	Assured Deep Multi-Agent Reinforcement Learning for Safe Robotic Systems. ICAART (Revised Selected Papers) Joshua Riley, Radu Calinescu, Colin Paterson, Daniel Kudenko, Alec Banks
2021	J	`jnl`	Improving cold-start recommendations using item-based stereotypes. User Model. User Adapt. Interact. Nourah A. ALRossais, Daniel Kudenko, Tommy Yuan
2021	—	`conf`	Reinforcement Learning with Quantitative Verification for Assured Multi-Agent Policies. ICAART (2) Joshua Riley, Radu Calinescu, Colin Paterson, Daniel Kudenko, Alec Banks
2021	B	`conf`	Utilising Assured Multi-Agent Reinforcement Learning within Safety-Critical Scenarios. KES Joshua Riley, Radu Calinescu, Colin Paterson, Daniel Kudenko, Alec Banks
2020	J	`jnl`	A comparative evaluation of machine learning methods for robot navigation through human crowds. CoRR Anastasia Gaydashenko, Daniel Kudenko, Aleksei Shpilman
2020	C	`conf`	Automatic Similarity Detection in LEGO Ducks. ICCC Mark Ferguson, Sebastian Deterding, Andreas Lieberoth, Marc Malmdorf Andersen, Sam Devlin, Daniel Kudenko, James Alfred Walker
2020	J	`jnl`	Continuous Gesture Recognition from sEMG Sensor Data with Recurrent Neural Networks and Adversarial Domain Adaptation. CoRR Ivan Sosin, Daniel Kudenko, Aleksei Shpilman
2020	J	`jnl`	Curriculum Learning with a Progression Function. CoRR Andrea Bassich, Francesco Foglino, Matteo Leonetti, Daniel Kudenko
2020	J	`jnl`	Deep Learning of Cell Classification using Microscope Images of Intracellular Microtubule Networks. CoRR Aleksei Shpilman, Dmitry Boikiy, Marina Polyakova, Daniel Kudenko, Anton Burakov, Elena Nadezhdina
2020	J	`jnl`	Deep Reinforcement Learning with Graph-based State Representations. CoRR Vikram Waradpande, Daniel Kudenko, Megha Khosla
2020	J	`jnl`	Learning to Run with Potential-Based Reward Shaping and Demonstrations from Video Data. CoRR Aleksandra Malysheva, Daniel Kudenko, Aleksei Shpilman
2020	J	`jnl`	MAGNet: Multi-agent Graph Network for Deep Multi-agent Reinforcement Learning. CoRR Aleksandra Malysheva, Daniel Kudenko, Aleksei Shpilman
2020	C	`conf`	Player Style Clustering without Game Variables. FDG Mark Ferguson, Sam Devlin, Daniel Kudenko, James Alfred Walker
2020	J	`jnl`	Predictive scheduling of wet flue gas desulfurization system based on reinforcement learning. Comput. Chem. Eng. Zhuang Shao, Fengqi Si, Daniel Kudenko, Peng Wang, Xiaozhong Tong
2020	J	`jnl`	Uniform State Abstraction For Reinforcement Learning. CoRR John Burden, Daniel Kudenko
2020	A	`conf`	Uniform State Abstraction for Reinforcement Learning. ECAI John Burden, Daniel Kudenko
2019	J	`jnl`	Artificial Intelligence for Prosthetics - challenge solutions. CoRR Lukasz Kidzinski, Carmichael F. Ong, Sharada Prasanna Mohanty, Jennifer L. Hicks, Sean F. Carroll, Bo Zhou, Hongsheng Zeng, Fan Wang, Rongzhong Lian, Hao Tian, Wojciech Jaskowski, Garrett Andersen, Odd Rune Lykkebø, Nihat Engin Toklu, Pranav Shyam, Rupesh Kumar Srivastava, Sergey Kolesnikov, Oleksii Hrinchuk, Anton Pechenko, Mattias Ljungström, Zhen Wang, Xu Hu, Zehong Hu, Minghui Qiu, Jun Huang, Aleksei Shpilman, Ivan Sosin, Oleg Svidchenko, Aleksandra Malysheva, Daniel Kudenko, Lance Rane, Aditya Bhatt, Zhengfei Wang, Penghui Qi, Zeyang Yu, Peng Peng, Quan Yuan, Wenxin Li, Yunsheng Tian, Ruihan Yang, Pingchuan Ma, Shauharda Khadka, Somdeb Majumdar, Zach Dwiel, Yinyin Liu, Evren Tumer, Jeremy D. Watson, Marcel Salathé, Sergey Levine, Scott L. Delp
2019	—	`conf`	Generating Stereotypes Automatically For Complex Categorical Features. KaRS@CIKM Nourah A. ALRossais, Daniel Kudenko
2019	J	`jnl`	Generating Stereotypes Automatically For Complex Categorical Features. CoRR Nourah A. ALRossais, Daniel Kudenko
2019	J	`jnl`	Guest Editorial: Special Issue on Intelligent Robotics and Multi-Agent Systems. Cybern. Syst. Rui Paulo Rocha, Daniel Kudenko
2019	J	`jnl`	Introspective Q-learning and learning from demonstration. Knowl. Eng. Rev. Mao Li, Tim Brys, Daniel Kudenko
2019	Misc	`conf`	MAGNet: Multi-agent Graph Network for Deep Multi-agent Reinforcement Learning. REDUNDANCY Aleksandra Malysheva, Daniel Kudenko, Aleksei Shpilman
2019	—	`conf`	Reinforcement Learning for Dialogue Game Based Argumentation. CMNA@PERSUASIVE Sultan Alahmari, Tommy Yuan, Daniel Kudenko
2019	—	`conf`	Reinforcement Learning of Dialogue Coherence and Relevance. CMNA@PERSUASIVE Sultan Alahmari, Tommy Yuan, Daniel Kudenko
2019	J	`jnl`	Resource Abstraction for Reinforcement Learning in Multiagent Congestion Problems. CoRR Kleanthis Malialis, Sam Devlin, Daniel Kudenko
2019	J	`jnl`	Two-level Q-learning: learning from conflict demonstrations. Knowl. Eng. Rev. Mao Li, Yi Wei, Daniel Kudenko
2018	C	`conf`	A Comparative Evaluation of Machine Learning Methods for Robot Navigation Through Human Crowds. ICMLA Anastasia Gaydashenko, Daniel Kudenko, Aleksei Shpilman
2018	C	`conf`	Applying Cartesian Genetic Programming to Evolve Rules for Intrusion Detection System. IJCCI Hasanen Alyasiri, John A. Clark, Daniel Kudenko
2018	—	`conf`	Automated Refactoring of Object-Oriented Code Using Clustering Ensembles. AAAI Workshops Timofey Bryksin, Alexey Shpilman, Daniel Kudenko
2018	J	`jnl`	Behavioural realism and the activation of aggressive concepts in violent video games. Entertain. Comput. David Zendle, Daniel Kudenko, Paul A. Cairns
2018	C	`conf`	Continuous Gesture Recognition from sEMG Sensor Data with Recurrent Neural Networks and Adversarial Domain Adaptation. ICARCV Ivan Sosin, Daniel Kudenko, Aleksei Shpilman
2018	J	`jnl`	Deep Multi-Agent Reinforcement Learning with Relevance Graphs. CoRR Aleksandra Malysheva, Tegg Tae Kyong Sung, Chae-Bong Sohn, Daniel Kudenko, Aleksei Shpilman
2018	—	`conf`	Evaluating Stereotype and Non-Stereotype Recommender Systems. KaRS@RecSys Nourah A. ALRossais, Daniel Kudenko
2018	—	`conf`	Evolutionary Computation Algorithms for Detecting Known and Unknown Attacks. SecITC Hasanen Alyasiri, John A. Clark, Daniel Kudenko
2018	A	`conf`	Introspective Reinforcement Learning and Learning from Demonstration. AAMAS Mao Li, Tim Brys, Daniel Kudenko
2018	C	`conf`	Learning to Run with Potential-Based Reward Shaping and Demonstrations from Video Data. ICARCV Aleksandra Malysheva, Daniel Kudenko, Aleksei Shpilman
2018	J	`jnl`	No priming in video games. Comput. Hum. Behav. David Zendle, Paul A. Cairns, Daniel Kudenko
2018	—	`conf`	iSynchronizer: A Tool for Extracting, Integration and Analysis of MovieLens and IMDb Datasets. UMAP (Adjunct Publication) Nourah A. ALRossais, Daniel Kudenko
2017	C	`conf`	A Reinforcement Learning Based Workflow Application Scheduling Approach in Dynamic Cloud Environment. CollaborateCom Yi Wei, Daniel Kudenko, Shijun Liu, Li Pan, Lei Wu, Xiangxu Meng
2017	—	`conf`	Assured Reinforcement Learning with Formally Verified Abstract Policies. ICAART (2) George Mason, Radu Calinescu, Daniel Kudenko, Alec Banks
2017	C	`conf`	Deep Learning of Cell Classification Using Microscope Images of Intracellular Microtubule Networks. ICMLA Aleksei Shpilman, Dmitry Boikiy, Marina Polyakova, Daniel Kudenko, Anton Burakov, Elena Nadezhdina
2017	—	`conf`	Distribution Data Across Multiple Cloud Storage using Reinforcement Learning Method. ICAART (2) Abdullah Fayez H. Algarni, Daniel Kudenko
2017	—	`conf`	Reinforcement Learning for Argumentation: Describing a PhD Research. CMNA@ICAIL Sultan Alahmari, Tommy Yuan, Daniel Kudenko
2016	J	`jnl`	Context-sensitive reward shaping for sparse interaction multi-agent systems. Knowl. Eng. Rev. Yann-Michaël De Hauwere, Sam Devlin, Daniel Kudenko, Ann Nowé
2016	J	`jnl`	Overcoming incorrect knowledge in plan-based reward shaping. Knowl. Eng. Rev. Kyriakos Efthymiadis, Sam Devlin, Daniel Kudenko
2016	J	`jnl`	Plan-based reward shaping for multi-agent reinforcement learning. Knowl. Eng. Rev. Sam Devlin, Daniel Kudenko
2016	J	`jnl`	Potential-based reward shaping for finite horizon online POMDP planning. Auton. Agents Multi Agent Syst. Adam Eck, Leen-Kiat Soh, Sam Devlin, Daniel Kudenko
2016	A	`conf`	Resource Abstraction for Reinforcement Learning in Multiagent Congestion Problems. AAMAS Kleanthis Malialis, Sam Devlin, Daniel Kudenko
2015	J	`jnl`	Distributed reinforcement learning for adaptive and robust network intrusion response. Connect. Sci. Kleanthis Malialis, Sam Devlin, Daniel Kudenko
2015	J	`jnl`	Distributed response to network intrusions using multiagent reinforcement learning. Eng. Appl. Artif. Intell. Kleanthis Malialis, Daniel Kudenko
2015	Misc	`conf`	Higher Graphical Fidelity Decreases Players' Access to Aggressive Concepts in Violent Video Games. CHI PLAY David Zendle, Paul A. Cairns, Daniel Kudenko
2015	A	`conf`	Knowledge Revision for Reinforcement Learning with Abstract MDPs. AAMAS Kyriakos Efthymiadis, Daniel Kudenko
2015	—	`conf`	Predicting player disengagement and first purchase with event-frequency based data representation. CIG Hanting Xie, Sam Devlin, Daniel Kudenko, Peter I. Cowling
2014	C	`conf`	A Phylogenetic Classification of the Video-Game Industry's Business Model Ecosystem. PRO-VE Nikolaos Goumagias, Ignazio Cabras, Kiran Jude Fernandes, Feng Li, Alberto Nucciarelli, Peter I. Cowling, Sam Devlin, Daniel Kudenko
2014	J	`jnl`	A comparison of plan-based and abstract MDP reward shaping. Connect. Sci. Kyriakos Efthymiadis, Daniel Kudenko
2014	A*	`conf`	Combining Multiple Correlated Reward and Shaping Signals by Measuring Confidence. AAAI Tim Brys, Ann Nowé, Daniel Kudenko, Matthew E. Taylor
2014	A	`conf`	Coordinated Team Learning and Difference Rewards for Distributed Intrusion Response. ECAI Kleanthis Malialis, Sam Devlin, Daniel Kudenko
2014	—	`conf`	Game intelligence. CIG Sam Devlin, Peter I. Cowling, Daniel Kudenko, Nikolaos Goumagias, Alberto Nucciarelli, Ignazio Cabras, Kiran Jude Fernandes, Feng Li
2014	—	`conf`	Gaussian Process-Based Inferential Control System. SOCO-CISIS-ICEUTE Ali Abusnina, Daniel Kudenko, Rolf Roth
2014	C	`conf`	Improving Robustness of Gaussian Process-Based Inferential Control System Using Kernel Principle Component Analysis. ICMLA Ali Abusnina, Daniel Kudenko, Rolf Roth
2014	J	`jnl`	Interview with Peter Stone and Matthew E. Taylor. Künstliche Intell. Daniel Kudenko
2014	A	`conf`	Knowledge revision for reinforcement learning with abstract MDPs. AAMAS Kyriakos Efthymiadis, Sam Devlin, Daniel Kudenko
2014	B	`conf`	Multi-objectivization of reinforcement learning problems by reward shaping. IJCNN Tim Brys, Anna Harutyunyan, Peter Vrancx, Matthew E. Taylor, Daniel Kudenko, Ann Nowé
2014	A	`conf`	Potential-based difference rewards for multiagent reinforcement learning. AAMAS Sam Devlin, Logan Michael Yliniemi, Daniel Kudenko, Kagan Tumer
2014	—	`conf`	Predicting Player Disengagement in Online Games. CGW@ECAI Hanting Xie, Daniel Kudenko, Sam Devlin, Peter I. Cowling
2014	J	`jnl`	Special Issue on Transfer Learning. Künstliche Intell. Daniel Kudenko
2013	C	`conf`	Multiagent Router Throttling: Decentralized Coordinated Response Against DDoS Attacks. IAAI Kleanthis Malialis, Daniel Kudenko
2013	A	`conf`	Overcoming erroneous domain knowledge in plan-based reward shaping. AAMAS Kyriakos Efthymiadis, Sam Devlin, Daniel Kudenko
2013	A	`conf`	Potential-based reward shaping for POMDPs. AAMAS Adam Eck, Leen-Kiat Soh, Sam Devlin, Daniel Kudenko
2013	—	`conf`	Using plan-based reward shaping to learn strategies in StarCraft: Broodwar. CIG Kyriakos Efthymiadis, Daniel Kudenko
2012	—	`ch.`	Actor Bots. Believable Bots María Arinbjarnar, Daniel Kudenko
2012	A	`conf`	Dynamic potential-based reward shaping. AAMAS Sam Devlin, Daniel Kudenko
2011	J	`jnl`	An Empirical Study of Potential-Based Reward Shaping and Advice in Complex, Multi-Agent Systems. Adv. Complex Syst. Sam Devlin, Daniel Kudenko, Marek Grzes
2011	J	`jnl`	Innovative Integrated Architecture for Educational Games: Challenges and Merits. Trans. Edutainment Rania A. Hodhod, Paul A. Cairns, Daniel Kudenko
2011	A	`conf`	Multi-agent, reward shaping for RoboCup KeepAway. AAMAS Sam Devlin, Marek Grzes, Daniel Kudenko
2011	A	`conf`	Theoretical considerations of potential-based reward shaping for multi-agent systems. AAMAS Sam Devlin, Daniel Kudenko
2010	J	`jnl`	Adaptive Interactive Narrative Model to Teach Ethics. Int. J. Gaming Comput. Mediat. Simulations Rania A. Hodhod, Daniel Kudenko, Paul A. Cairns
2010	J	`jnl`	Automated Event Recognition for Football Commentary Generation. Int. J. Gaming Comput. Mediat. Simulations Maliang Zheng, Daniel Kudenko
2010	—	`conf`	Bayesian networks: Real-time applicable decision mechanisms for intelligent agents in interactive drama. CIG María Arinbjarnar, Daniel Kudenko
2010	Misc	`conf`	Character Education Using Pedagogical Agents and Socratic Voice. FLAIRS Rania A. Hodhod, Daniel Kudenko, Paul A. Cairns
2010	J	`jnl`	Online learning of shaping rewards in reinforcement learning. Neural Networks Marek Grzes, Daniel Kudenko
2010	A	`conf`	PAC-MDP learning with knowledge-based admissible models. AAMAS Marek Grzes, Daniel Kudenko
2010	—	`ch.`	Tuning an Algorithm Using Design of Experiments. Experimental Methods for the Analysis of Optimization Algorithms Enda Ridge, Daniel Kudenko
2009	B	`conf`	Duality of Actor and Character Goals in Virtual Drama. IVA María Arinbjarnar, Daniel Kudenko
2009	A	`conf`	Educational Narrative and Student Modeling for Ill-Defined Domains. AIED Rania A. Hodhod, Daniel Kudenko, Paul A. Cairns
2009	J	`jnl`	Finding Unexpected Navigation Behaviour in Clickstream Data for Website Design Improvement. J. Web Eng. I-Hsien Ting, Chris Kimble, Daniel Kudenko
2009	J	`jnl`	Generation of Adaptive Dilemma-Based Interactive Narratives. IEEE Trans. Comput. Intell. AI Games Heather Barber, Daniel Kudenko
2009	—	`conf`	Improving Optimistic Exploration in Model-Free Reinforcement Learning. ICANNGA Marek Grzes, Daniel Kudenko
2009	—	`conf`	Knowledge-Based Reinforcement Learning for Data Mining. ADMI Daniel Kudenko, Marek Grzes
2009	—	`conf`	Reinforcement Learning in RoboCup KeepAway with Partial Observability. IAT Sam Devlin, Marek Grzes, Daniel Kudenko
2009	J	`jnl`	Reinforcement Learning with Reward Shaping and Mixed Resolution Function Approximation. Int. J. Agent Technol. Syst. Marek Grzes, Daniel Kudenko
2009	C	`conf`	Theoretical and Empirical Analysis of Reward Shaping in Reinforcement Learning. ICMLA Marek Grzes, Daniel Kudenko
2008	—	`ed.`	Adaptive Agents and Multi-Agent Systems III. Adaptation and Multi-Agent Learning, 5th, 6th, and 7th European Symposium, ALAMAS 2005-2007 on Adaptive and Learning Agents and Multi-Agent Systems, Revised Selected Papers Adaptive Agents and Multi-Agent Systems Karl Tuyls, Ann Nowé, Zahia Guessoum, Daniel Kudenko
2008	Misc	`conf`	An Empirical Analysis of the Impact of Prioritised Sweeping on the DynaQ's Performance. ICAISC Marek Grzes, Daniel Kudenko
2008	—	`ch.`	Determining Whether a Problem Characteristic Affects Heuristic Performance. Recent Advances in Evolutionary Computation for Combinatorial Optimization Enda Ridge, Daniel Kudenko
2008	C	`conf`	Generation of Dilemma-Based Narratives: Method and Turing Test Evaluation. ICIDS Heather Barber, Daniel Kudenko
2008	—	`conf`	Generation of dilemma-based interactive narratives with a changeable story goal. INTETAIN Heather Barber, Daniel Kudenko
2008	—	`conf`	Multi-Agent Reinforcement Learning for Intrusion Detection: A Case Study and Evaluation. MATES Arturo Servin, Daniel Kudenko
2008	A	`conf`	Multi-Agent Reinforcement Learning for Intrusion Detection: A case study and evaluation. ECAI Arturo Servin, Daniel Kudenko
2008	—	`conf`	Multigrid Reinforcement Learning with Reward Shaping. ICANN (1) Marek Grzes, Daniel Kudenko
2008	Misc	`conf`	Robustness Analysis of SARSA(lambda): Different Models of Reward and Initialisation. AIMSA Marek Grzes, Daniel Kudenko
2008	C	`conf`	Schemas in Directed Emergent Drama. ICIDS María Arinbjarnar, Daniel Kudenko
2007	—	`conf`	APD-A Tool for Identifying Behavioural Patterns Automatically from Clickstream Data. KES (2) I-Hsien Ting, Lillian Clark, Chris Kimble, Daniel Kudenko, Peter C. Wright
2007	—	`ch.`	Adaptive Generation of Dilemma-based Interactive Narratives. Advanced Intelligent Paradigms in Computer Games Heather Barber, Daniel Kudenko
2007	B	`conf`	An Analysis of Problem Difficulty for a Class of Optimisation Heuristics. EvoCOP Enda Ridge, Daniel Kudenko
2007	A	`conf`	Analyzing heuristic performance with response surface models: prediction, optimization and robustness. GECCO Enda Ridge, Daniel Kudenko
2007	B	`conf`	Applying Web Usage Mining Techniques to Discover Potential Browsing Problems of Users. ICALT I-Hsien Ting, Chris Kimble, Daniel Kudenko
2007	—	`conf`	Combining Reinforcement Learning with Symbolic Planning. Adaptive Agents and Multi-Agents Systems Matthew Jon Grounds, Daniel Kudenko
2007	—	`conf`	Dynamic Generation of Dilemma-based Interactive Narratives. AIIDE Heather Barber, Daniel Kudenko
2007	—	`conf`	Multi-agent Reinforcement Learning for Intrusion Detection. Adaptive Agents and Multi-Agents Systems Arturo Servin, Daniel Kudenko
2007	—	`conf`	Parallel Reinforcement Learning with Linear Function Approximation. Adaptive Agents and Multi-Agents Systems Matthew Jon Grounds, Daniel Kudenko
2007	A	`conf`	Parallel reinforcement learning with linear function approximation. AAMAS Matthew Jon Grounds, Daniel Kudenko
2007	A	`conf`	Screening the parameters affecting heuristic performance. GECCO Enda Ridge, Daniel Kudenko
2007	J	`jnl`	Special issue on Nature-inspired systems for parallel, asynchronous and decentralised environments. Multiagent Grid Syst. Enda Ridge, Edward Curry, Daniel Kudenko, Dimitar Kazakov
2007	—	`conf`	Tuning the Performance of the MMAS Heuristic. SLS Enda Ridge, Daniel Kudenko
2006	B	`conf`	A Study of Concurrency in the Ant Colony System Algorithm. IEEE Congress on Evolutionary Computation Enda Ridge, Daniel Kudenko, Dimitar Kazakov
2006	J	`jnl`	Combining ethnographic and clickstream data to identify user Web browsing strategies. Inf. Res. Lillian Clark, I-Hsien Ting, Chris Kimble, Peter C. Wright, Daniel Kudenko
2006	—	`conf`	Interactions Between Stereotypes. AH Zoë P. Lock, Daniel Kudenko
2005	C	`conf`	A Pattern Restore Method for Restoring Missing Patterns in Server Side Clickstream Data. APWeb I-Hsien Ting, Chris Kimble, Daniel Kudenko
2005	—	`ed.`	Adaptive Agents and Multi-Agent Systems II: Adaptation and Multi-Agent Learning Adaptive Agents and Multi-Agent Systems Daniel Kudenko, Dimitar Kazakov, Eduardo Alonso
2005	—	`conf`	Baselines for Joint-Action Reinforcement Learning of Coordination in Cooperative Multi-agent Systems. Adaptive Agents and Multi-Agent Systems Martin Carpenter, Daniel Kudenko
2005	—	`conf`	Learning to Coordinate Using Commitment Sequences in Cooperative Multi-agent Systems. Adaptive Agents and Multi-Agent Systems Spiros Kapetanakis, Daniel Kudenko, Malcolm J. A. Strens
2005	—	`conf`	Moving Nature-Inspired Algorithms to Parallel, Asynchronous and Decentralised Environments. SOAS Enda Ridge, Daniel Kudenko, Dimitar Kazakov, Edward Curry
2005	—	`conf`	Reinforcement Learning of Coordination in Heterogeneous Cooperative Multi-agent Systems. Adaptive Agents and Multi-Agent Systems Spiros Kapetanakis, Daniel Kudenko
2005	—	`conf`	UBB Mining: Finding Unexpected Browsing Behaviour in Clickstream Data to Improve a Web Site's Design. Web Intelligence I-Hsien Ting, Chris Kimble, Daniel Kudenko
2004	A	`conf`	Algorithms for Distributed Exploration. ECAI Thomas Walker, Daniel Kudenko, Malcolm J. A. Strens
2004	A	`conf`	Reinforcement Learning of Coordination in Heterogeneous Cooperative Multi-Agent Systems. AAMAS Spiros Kapetanakis, Daniel Kudenko
2003	—	`ed.`	Adaptive Agents and Multi-Agent Systems: Adaptation and Multi-Agent Learning Adaptive Agents and Multi-Agent Systems Eduardo Alonso, Daniel Kudenko, Dimitar Kazakov
2003	—	`conf`	Group Decision Making through Mediated Discussions. User Modeling Daniel Kudenko, Mathias Bauer, Dietmar Dengler
2003	—	`conf`	MIAU - Supporting Group Decisions in E-Commerce Applications. HCI (4) Stephan Baldes, Mathias Bauer, Dietmar Dengler, Daniel Kudenko, Gabriele Paul, Thomas Rist, Christian Schmitt
2002	—	`conf`	Reinforcement Learning Approaches to Coordination in Cooperative Multi-agent Systems. Adaptive Agents and Multi-Agents Systems Spiros Kapetanakis, Daniel Kudenko, Malcolm J. A. Strens
2002	—	`conf`	Reinforcement Learning of Coordination in Cooperative Multi-Agent Systems. AAAI/IAAI Spiros Kapetanakis, Daniel Kudenko
2001	J	`jnl`	Learning in multi-agent systems. Knowl. Eng. Rev. Eduardo Alonso, Mark d'Inverno, Daniel Kudenko, Michael Luck, Jason Noble
2001	—	`conf`	Machine Learning and Inductive Logic Programming for Multi-agent Systems. EASSS Dimitar Kazakov, Daniel Kudenko
2001	J	`jnl`	Sistemas Logicos de Multiples Agentes: Arquitectura e Implementacion en Simuladores de Conflictos. Inteligencia Artif. Eduardo Alonso, Daniel Kudenko
2000	—	`conf`	Machine Learning for Logic-Based Multi-agent Systems. FAABS Eduardo Alonso, Daniel Kudenko
1999	—	`conf`	Feature-Based Learners for Description Logics. Description Logics Daniel Kudenko, Haym Hirsh
1998	—	`conf`	Feature Generation for Sequence Categorization. AAAI/IAAI Daniel Kudenko, Haym Hirsh
1997	—	`conf`	Representing Sequences in Description Logics. AAAI/IAAI Haym Hirsh, Daniel Kudenko
1997	—	`conf`	Transferring and Retraining Learned Information Filters. AAAI/IAAI William W. Cohen, Daniel Kudenko
1996	—	`conf`	Representing Sequences in Description Logics Using Suffix Trees. Description Logics Daniel Kudenko, Haym Hirsh
1994	J	`jnl`	An Empirical Analysis of Terminological Representation Systems. Artif. Intell. Jochen Heinsohn, Daniel Kudenko, Bernhard Nebel, Hans-Jürgen Profitlich
1992	A*	`conf`	An Empirical Analysis of Terminological Representation Systems. AAAI Jochen Heinsohn, Daniel Kudenko, Bernhard Nebel, Hans-Jürgen Profitlich