| Dynamic potential-based reward shaping SM Devlin, D Kudenko Proceedings of the 11th International Conference on Autonomous Agents and …, 2012 | 106 | 2012 |
| Theoretical considerations of potential-based reward shaping for multi-agent systems S Devlin, D Kudenko The 10th International Conference on Autonomous Agents and Multiagent …, 2011 | 87 | 2011 |
| 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 | 70 | 2014 |
| 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 (ACS) 14 (02), 251-278, 2011 | 69 | 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 | 56 | 2017 |
| 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 | 46 | 2015 |
| Expressing Arbitrary Reward Functions as Potential-Based Advice. A Harutyunyan, S Devlin, P Vrancx, A Nowé AAAI, 2652-2658, 2015 | 34 | 2015 |
| Dynamic economic emissions dispatch optimisation using multi-agent reinforcement learning P Mannion, K Mason, S Devlin, J Duggan, E Howley Proceedings of the Adaptive and Learning Agents workshop (at AAMAS 2016), 2016 | 23 | 2016 |
| Resource abstraction for reinforcement learning in multiagent congestion problems K Malialis, S Devlin, D Kudenko arXiv preprint arXiv:1903.05431, 2019 | 22 | 2019 |
| Multi-objective dynamic dispatch optimisation using multi-agent reinforcement learning P Mannion, K Mason, S Devlin, J Duggan, E Howley Proceedings of the 2016 International Conference on Autonomous Agents …, 2016 | 22 | 2016 |
| Policy invariance under reward transformations for multi-objective reinforcement learning P Mannion, S Devlin, K Mason, J Duggan, E Howley Neurocomputing 263, 60-73, 2017 | 20 | 2017 |
| 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 (3), 403-445, 2016 | 20 | 2016 |
| Combining Gameplay Data with Monte Carlo Tree Search to Emulate Human Play. S Devlin, A Anspoka, N Sephton, PI Cowling, J Rollason AIIDE, 16-22, 2016 | 18 | 2016 |
| 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 | 18 | 2014 |
| Knowledge revision for reinforcement learning with abstract MDPs K Efthymiadis, S Devlin, D Kudenko Proceedings of the 2014 international conference on Autonomous agents and …, 2014 | 16 | 2014 |
| Player preference and style in a leading mobile card game P Cowling, S Devlin, E Powley, D Whitehouse, J Rollason IEEE Transactions on Computational Intelligence and AI in Games 7 (3), 233-242, 2015 | 15 | 2015 |
| Multi-agent, reward shaping for robocup keepaway S Devlin, M Grześ, D Kudenko The 10th International Conference on Autonomous Agents and Multiagent …, 2011 | 15 | 2011 |
| Exploring survival rates of companies in the UK video-games industry: An empirical study I Cabras, ND Goumagias, K Fernandes, P Cowling, F Li, D Kudenko, ... Technological forecasting and social change 117, 305-314, 2017 | 14 | 2017 |
| Narrative bytes: Data-driven content production in esports F Block, V Hodge, S Hobson, N Sephton, S Devlin, MF Ursu, A Drachen, ... Proceedings of the 2018 ACM International Conference on Interactive …, 2018 | 12 | 2018 |
| Type inference in flexible model-driven engineering A Zolotas, N Matragkas, S Devlin, DS Kolovos, RF Paige European Conference on Modelling Foundations and Applications, 75-91, 2015 | 12 | 2015 |
Daniel KudenkoL3S Research Center, Leibniz University Hannover, GermanyVerified email at l3s.de
