Daniel Kudenko

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Sam DevlinMicrosoft Research CambridgeVerified email at microsoft.com
Marek GrześSenior Lecturer, School of Computing, University of KentVerified email at kent.ac.uk
Eduardo AlonsoProfessor of Artificial Intelligence; City, University of LondonVerified email at city.ac.uk
Chris KimbleVerified email at chris-kimble.com
Enda RidgeGoogleVerified email at google.com
Ignazio CabrasNewcastle Business School, Northumbria UniversityVerified email at northumbria.ac.uk
Paul CairnsProfessor of Human-Computer Interaction, University of YorkVerified email at york.ac.uk
Professor Feng LiAssociate Dean for Research, Bayes Business School (Formerly Cass), City, University of LondonVerified email at city.ac.uk
Kiran FernandesDurham University Business SchoolVerified email at durham.ac.uk
I-HSIEN TINGProfessor, Department of Information Management, National University of Kaohsiung, TaiwanVerified email at nuk.edu.tw
Alberto NucciarelliUniversity of TrentoVerified email at unitn.it
Kleanthis MalialisKIOS Research and Innovation Center of Excellence, University of CyprusVerified email at ucy.ac.cy
Radu CalinescuProfessor of Computer Science, University of YorkVerified email at york.ac.uk
Nowe AnnGewoon hoogleraarVerified email at vub.be
Maria ArinbjarnarPhd Student, the University of YorkVerified email at york.ac.uk
Kyriakos EfthymiadisPatent Examiner at European Patent OfficeVerified email at vub.be
Tim BrysVrije Universiteit Brussel; Action Research AssociatesVerified email at ai.vub.ac.be
Hans-Jürgen ProfitlichGerman Research Center for Artificial Intelligence, DFKI, Saarland Informatics Campus, SICVerified email at dfki.de
Peter WrightProfessor of Social Computing University of NewcastleVerified email at ncl.ac.uk
Matthew E. TaylorProfessor, University of AlbertaVerified email at ualberta.ca

Daniel Kudenko

L3S Research Center, Leibniz University Hannover, Germany

Verified email at l3s.de - Homepage

Artificial Intelligence Machine Learning Reinforcement Learning Mult-Agent Systems Interactive Drama


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Reinforcement learning of coordination in heterogeneous cooperative multi-agent systems S Kapetanakis, D Kudenko Symposium on Adaptive Agents and Multi-agent Systems, 119-131, 2003	326	2003
Potential-based difference rewards for multiagent reinforcement learning S Devlin, L Yliniemi, D Kudenko, K Tumer Proceedings of the 2014 international conference on Autonomous agents and …, 2014	261	2014
Dynamic potential-based reward shaping SM Devlin, D Kudenko 11th International Conference on Autonomous Agents and Multiagent Systems …, 2012	260	2012
Learning in multi-agent systems E Alonso, M d'Inverno, D Kudenko, M Luck, J Noble The Knowledge Engineering Review 16 (3), 277-284, 2001	197	2001
Potential-based reward shaping for finite horizon online POMDP planning A Eck, LK Soh, S Devlin, D Kudenko Autonomous Agents and Multi-Agent Systems 30, 403-445, 2016	180	2016
Theoretical considerations of potential-based reward shaping for multi-agent systems S Devlin, D Kudenko Tenth International Conference on Autonomous Agents and Multi-Agent Systems …, 2011	159	2011
From value chains to technological platforms: The effects of crowdfunding in the digital game industry A Nucciarelli, F Li, KJ Fernandes, N Goumagias, I Cabras, S Devlin, ... Journal of Business Research 78, 341-352, 2017	154	2017
An empirical analysis of terminological representation systems J Heinsohn, D Kudenko, B Nebel, HJ Profitlich Artificial Intelligence 68 (2), 367-397, 1994	129	1994
An empirical study of potential-based reward shaping and advice in complex, multi-agent systems S Devlin, D Kudenko, M Grześ Advances in Complex Systems 14 (02), 251-278, 2011	108	2011
Multi-agent reinforcement learning for intrusion detection A Servin, D Kudenko European Symposium on Adaptive Agents and Multi-Agent Systems, 211-223, 2005	108	2005
Plan-based reward shaping for reinforcement learning M Grzes, D Kudenko 2008 4th International IEEE Conference Intelligent Systems 2, 10-22-10-29, 2008	104	2008
Game intelligence S Devlin, PI Cowling, D Kudenko, N Goumagias, A Nucciareli, I Cabras, ... 2014 IEEE Conference on Computational Intelligence and Games, 1-8, 2014	98	2014
Dynamic generation of dilemma-based interactive narratives H Barber, D Kudenko Proceedings of the AAAI Conference on Artificial Intelligence and …, 2007	98	2007
Multi-objectivization of reinforcement learning problems by reward shaping T Brys, A Harutyunyan, P Vrancx, ME Taylor, D Kudenko, A Nowé 2014 international joint conference on neural networks (IJCNN), 2315-2322, 2014	94	2014
Online learning of shaping rewards in reinforcement learning M Grześ, D Kudenko Neural networks 23 (4), 541-550, 2010	90	2010
Tuning the performance of the MMAS heuristic E Ridge, D Kudenko International Workshop on Engineering Stochastic Local Search Algorithms, 46-60, 2007	74	2007
Distributed response to network intrusions using multiagent reinforcement learning K Malialis, D Kudenko Engineering Applications of Artificial Intelligence 41, 270-284, 2015	72	2015
Predicting player disengagement and first purchase with event-frequency based data representation H Xie, S Devlin, D Kudenko, P Cowling 2015 IEEE conference on computational intelligence and games (CIG), 230-237, 2015	71	2015
Combining reinforcement learning with symbolic planning M Grounds, D Kudenko European Symposium on Adaptive Agents and Multi-Agent Systems, 75-86, 2005	69	2005
Machine learning and inductive logic programming for multi-agent systems D Kazakov, D Kudenko⋆ ECCAI Advanced Course on Artificial Intelligence, 246-270, 2001	69	2001

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