Daniel Kudenko

Sam Devlin, Daniel Kudenko: Dynamic potential-based reward shaping. AAMAS 2012: 433-440

Sam Devlin, Daniel Kudenko, Marek Grzes: An Empirical Study of Potential-Based Reward Shaping and Advice in Complex, Multi-Agent Systems. Advances in Complex Systems 14(2): 251-278 (2011)

Rania A. HodHod, Paul A. Cairns, Daniel Kudenko: Innovative Integrated Architecture for Educational Games: Challenges and Merits. T. Edutainment 5: 1-34 (2011)

Sam Devlin, Daniel Kudenko: Theoretical considerations of potential-based reward shaping for multi-agent systems. AAMAS 2011: 225-232

Sam Devlin, Marek Grzes, Daniel Kudenko: Multi-agent, reward shaping for RoboCup KeepAway. AAMAS 2011: 1227-1228

Rania A. HodHod, Daniel Kudenko, Paul A. Cairns: Adaptive Interactive Narrative Model to Teach Ethics. IJGCMS 2(4): 1-15 (2010)

Maliang Zheng, Daniel Kudenko: Automated Event Recognition for Football Commentary Generation. IJGCMS 2(4): 67-84 (2010)

Marek Grzes, Daniel Kudenko: Online learning of shaping rewards in reinforcement learning. Neural Networks 23(4): 541-550 (2010)

Marek Grzes, Daniel Kudenko: PAC-MDP learning with knowledge-based admissible models. AAMAS 2010: 349-358

María Arinbjarnar, Daniel Kudenko: Bayesian networks: Real-time applicable decision mechanisms for intelligent agents in interactive drama. CIG 2010: 427-434

Rania A. HodHod, Daniel Kudenko, Paul A. Cairns: Character Education Using Pedagogical Agents and Socratic Voice. FLAIRS Conference 2010

Marek Grzes, Daniel Kudenko: Reinforcement Learning with Reward Shaping and Mixed Resolution Function Approximation. IJATS 1(2): 36-54 (2009)

I-Hsien Ting, Chris Kimble, Daniel Kudenko: Finding Unexpected Navigation Behaviour in Clickstream Data for Website Design Improvement. J. Web Eng. 8(1): 71-92 (2009)

Heather Barber, Daniel Kudenko: Generation of Adaptive Dilemma-Based Interactive Narratives. IEEE Trans. Comput. Intellig. and AI in Games 1(4): 309-326 (2009)

Daniel Kudenko, Marek Grzes: Knowledge-Based Reinforcement Learning for Data Mining. ADMI 2009: 21-22

Rania A. HodHod, Daniel Kudenko, Paul A. Cairns: Educational Narrative and Student Modeling for Ill-Defined Domains. AIED 2009: 638-640

Sam Devlin, Marek Grzes, Daniel Kudenko: Reinforcement Learning in RoboCup KeepAway with Partial Observability. IAT 2009: 201-208

Marek Grzes, Daniel Kudenko: Improving Optimistic Exploration in Model-Free Reinforcement Learning. ICANNGA 2009: 360-369

Marek Grzes, Daniel Kudenko: Theoretical and Empirical Analysis of Reward Shaping in Reinforcement Learning. ICMLA 2009: 337-344

María Arinbjarnar, Daniel Kudenko: Duality of Actor and Character Goals in Virtual Drama. IVA 2009: 386-392

Marek Grzes, Daniel Kudenko: Robustness Analysis of SARSA(lambda): Different Models of Reward and Initialisation. AIMSA 2008: 144-156

Arturo Servin, Daniel Kudenko: Multi-Agent Reinforcement Learning for Intrusion Detection: A case study and evaluation. ECAI 2008: 873-874

Marek Grzes, Daniel Kudenko: An Empirical Analysis of the Impact of Prioritised Sweeping on the DynaQ's Performance. ICAISC 2008: 1041-1051

Marek Grzes, Daniel Kudenko: Multigrid Reinforcement Learning with Reward Shaping. ICANN (1) 2008: 357-366

María Arinbjarnar, Daniel Kudenko: Schemas in Directed Emergent Drama. ICIDS 2008: 180-185

Heather Barber, Daniel Kudenko: Generation of Dilemma-Based Narratives: Method and Turing Test Evaluation. ICIDS 2008: 214-217

Arturo Servin, Daniel Kudenko: Multi-Agent Reinforcement Learning for Intrusion Detection: A Case Study and Evaluation. MATES 2008: 159-170

Enda Ridge, Daniel Kudenko: Determining Whether a Problem Characteristic Affects Heuristic Performance. Recent Advances in Evolutionary Computation for Combinatorial Optimization 2008: 21-35

Karl Tuyls, Ann Nowé, Zahia Guessoum, Daniel Kudenko (Eds.): 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. Lecture Notes in Computer Science 4865, Springer 2008, isbn 978-3-540-77947-6

Enda Ridge, Edward Curry, Daniel Kudenko, Dimitar Kazakov: Special issue on Nature-inspired systems for parallel, asynchronous and decentralised environments. Multiagent and Grid Systems 3(1): 1-2 (2007)

Matthew Grounds, Daniel Kudenko: Parallel Reinforcement Learning with Linear Function Approximation. Adaptive Agents and Multi-Agents Systems 2007: 60-74

Matthew Grounds, Daniel Kudenko: Combining Reinforcement Learning with Symbolic Planning. Adaptive Agents and Multi-Agents Systems 2007: 75-86

Arturo Servin, Daniel Kudenko: Multi-agent Reinforcement Learning for Intrusion Detection. Adaptive Agents and Multi-Agents Systems 2007: 211-223

Heather Barber, Daniel Kudenko: Dynamic Generation of Dilemma-based Interactive Narratives. AIIDE 2007: 2-7

Matthew Grounds, Daniel Kudenko: Parallel reinforcement learning with linear function approximation. AAMAS 2007: 45

Enda Ridge, Daniel Kudenko: An Analysis of Problem Difficulty for a Class of Optimisation Heuristics. EvoCOP 2007: 198-209

Enda Ridge, Daniel Kudenko: Analyzing heuristic performance with response surface models: prediction, optimization and robustness. GECCO 2007: 150-157

Enda Ridge, Daniel Kudenko: Screening the parameters affecting heuristic performance. GECCO 2007: 180

I-Hsien Ting, Chris Kimble, Daniel Kudenko: Applying Web Usage Mining Techniques to Discover Potential Browsing Problems of Users. ICALT 2007: 929-930

I-Hsien Ting, Lillian Clark, Chris Kimble, Daniel Kudenko, Peter Wright: APD-A Tool for Identifying Behavioural Patterns Automatically from Clickstream Data. KES (2) 2007: 66-73

Enda Ridge, Daniel Kudenko: Tuning the Performance of the MMAS Heuristic. SLS 2007: 46-60

Heather Barber, Daniel Kudenko: Adaptive Generation of Dilemma-based Interactive Narratives. Advanced Intelligent Paradigms in Computer Games 2007: 19-37

Lillian Clark, I-Hsien Ting, Chris Kimble, Peter Wright, Daniel Kudenko: Combining ethnographic and clickstream data to identify user Web browsing strategies. Inf. Res. 11(2) (2006)

Zoë P. Lock, Daniel Kudenko: Interactions Between Stereotypes. AH 2006: 172-181

Martin Carpenter, Daniel Kudenko: Baselines for Joint-Action Reinforcement Learning of Coordination in Cooperative Multi-agent Systems. Adaptive Agents and Multi-Agent Systems 2005: 55-72

Spiros Kapetanakis, Daniel Kudenko, Malcolm J. A. Strens: Learning to Coordinate Using Commitment Sequences in Cooperative Multi-agent Systems. Adaptive Agents and Multi-Agent Systems 2005: 106-118

Spiros Kapetanakis, Daniel Kudenko: Reinforcement Learning of Coordination in Heterogeneous Cooperative Multi-agent Systems. Adaptive Agents and Multi-Agent Systems 2005: 119-131

I-Hsien Ting, Chris Kimble, Daniel Kudenko: A Pattern Restore Method for Restoring Missing Patterns in Server Side Clickstream Data. APWeb 2005: 501-512

Enda Ridge, Daniel Kudenko, Dimitar Kazakov, Edward Curry: Moving Nature-Inspired Algorithms to Parallel, Asynchronous and Decentralised Environments. SOAS 2005: 35-49

I-Hsien Ting, Chris Kimble, Daniel Kudenko: UBB Mining: Finding Unexpected Browsing Behaviour in Clickstream Data to Improve a Web Site's Design. Web Intelligence 2005: 179-185

Daniel Kudenko, Dimitar Kazakov, Eduardo Alonso (Eds.): Adaptive Agents and Multi-Agent Systems II: Adaptation and Multi-Agent Learning. Lecture Notes in Computer Science 3394, Springer 2005, isbn 3-540-25260-6

Spiros Kapetanakis, Daniel Kudenko: Reinforcement Learning of Coordination in Heterogeneous Cooperative Multi-Agent Systems. AAMAS 2004: 1258-1259

Thomas Walker, Daniel Kudenko, Malcolm J. A. Strens: Algorithms for Distributed Exploration. ECAI 2004: 84-88

Daniel Kudenko, Mathias Bauer, Dietmar Dengler: Group Decision Making through Mediated Discussions. User Modeling 2003: 238-247

Eduardo Alonso, Daniel Kudenko, Dimitar Kazakov (Eds.): Adaptive Agents and Multi-Agent Systems: Adaptation and Multi-Agent Learning. Lecture Notes in Computer Science 2636, Springer 2003, isbn 3-540-40068-0

Spiros Kapetanakis, Daniel Kudenko: Reinforcement Learning of Coordination in Cooperative Multi-Agent Systems. AAAI/IAAI 2002: 326-331

Spiros Kapetanakis, Daniel Kudenko, Malcolm J. A. Strens: Reinforcement Learning Approaches to Coordination in Cooperative Multi-agent Systems. Adaptive Agents and Multi-Agents Systems 2002: 18-32

Eduardo Alonso, Daniel Kudenko: Sistemas Logicos de Multiples Agentes: Arquitectura e Implementacion en Simuladores de Conflictos. Inteligencia Artificial, Revista Iberoamericana de Inteligencia Artificial 5(13): 85-93 (2001)

Dimitar Kazakov, Daniel Kudenko: Machine Learning and Inductive Logic Programming for Multi-agent Systems. EASSS 2001: 246-272

Eduardo Alonso, Daniel Kudenko: Machine Learning for Logic-Based Multi-agent Systems. FAABS 2000: 306-307

Daniel Kudenko, Haym Hirsh: Feature-Based Learners for Description Logics. Description Logics 1999

Daniel Kudenko, Haym Hirsh: Feature Generation for Sequence Categorization. AAAI/IAAI 1998: 733-738

Haym Hirsh, Daniel Kudenko: Representing Sequences in Description Logics. AAAI/IAAI 1997: 384-389

William W. Cohen, Daniel Kudenko: Transferring and Retraining Learned Information Filters. AAAI/IAAI 1997: 583-590

Daniel Kudenko, Haym Hirsh: Representing Sequences in Description Logics Using Suffix Trees. Description Logics 1996: 141-145

Jochen Heinsohn, Daniel Kudenko, Bernhard Nebel, Hans-Jürgen Profitlich: An Empirical Analysis of Terminological Representation Systems. Artif. Intell. 68(2): 367-397 (1994)

Jochen Heinsohn, Daniel Kudenko, Bernhard Nebel, Hans-Jürgen Profitlich: An Empirical Analysis of Terminological Representation Systems. AAAI 1992: 767-773