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Pablo Hernandez-Leal
Pablo Hernandez-Leal
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Zitiert von
Zitiert von
Jahr
A survey and critique of multiagent deep reinforcement learning
P Hernandez-Leal, B Kartal, ME Taylor
Autonomous Agents and Multi-Agent Systems 33 (6), 750-797, 2019
758*2019
A survey of learning in multiagent environments: Dealing with non-stationarity
P Hernandez-Leal, M Kaisers, T Baarslag, EM De Cote
arXiv preprint arXiv:1707.09183, 2017
3532017
Local energy markets: Paving the path toward fully transactive energy systems
F Lezama, J Soares, P Hernandez-Leal, M Kaisers, T Pinto, Z Vale
IEEE Transactions on Power Systems 34 (5), 4081-4088, 2018
3482018
Multi-label classification with Bayesian network-based chain classifiers
LE Sucar, C Bielza, EF Morales, P Hernandez-Leal, JH Zaragoza, ...
Pattern Recognition Letters 41, 14-22, 2014
1472014
Uncertainty-aware action advising for deep reinforcement learning agents
FL Da Silva, P Hernandez-Leal, B Kartal, ME Taylor
Proceedings of the AAAI conference on artificial intelligence 34 (04), 5792-5799, 2020
962020
Stress modelling and prediction in presence of scarce data
A Maxhuni, P Hernandez-Leal, LE Sucar, V Osmani, EF Morales, ...
Journal of biomedical informatics 63, 344-356, 2016
862016
Agent modeling as auxiliary task for deep reinforcement learning
P Hernandez-Leal, B Kartal, ME Taylor
Proceedings of the AAAI conference on artificial intelligence and …, 2019
582019
Efficiently detecting switches against non-stationary opponents
P Hernandez-Leal, Y Zhan, ME Taylor, LE Sucar, E Munoz de Cote
Autonomous Agents and Multi-Agent Systems 31, 767-789, 2017
442017
Terminal prediction as an auxiliary task for deep reinforcement learning
B Kartal, P Hernandez-Leal, ME Taylor
Proceedings of the AAAI Conference on Artificial Intelligence and …, 2019
392019
Identifying and tracking switching, non-stationary opponents: A Bayesian approach
P Hernandez-Leal, ME Taylor, BS Rosman, LE Sucar, E Munoz de Cote
Association for the Advancement of Artificial Intelligence (AAAI), 2016
382016
Cdt: Cascading decision trees for explainable reinforcement learning
Z Ding, P Hernandez-Leal, GW Ding, C Li, R Huang
arXiv preprint arXiv:2011.07553, 2020
362020
Towards a fast detection of opponents in repeated stochastic games
P Hernandez-Leal, M Kaisers
Autonomous Agents and Multiagent Systems: AAMAS 2017 Workshops, Best Papers …, 2017
352017
InstanceRank based on borders for instance selection
P Hernandez-Leal, JA Carrasco-Ochoa, JF Martínez-Trinidad, ...
Pattern Recognition 46 (1), 365-375, 2013
342013
Learning against sequential opponents in repeated stochastic games
P Hernandez-Leal, M Kaisers
The 3rd Multi-disciplinary Conference on Reinforcement Learning and Decision …, 2017
292017
Action guidance with MCTS for deep reinforcement learning
B Kartal, P Hernandez-Leal, ME Taylor
Proceedings of the AAAI conference on artificial intelligence and …, 2019
272019
A framework for learning and planning against switching strategies in repeated games
P Hernandez-Leal, E Munoz de Cote, LE Sucar
Connection Science 26 (2), 103-122, 2014
272014
Learning temporal nodes Bayesian networks
P Hernandez-Leal, JA Gonzalez, EF Morales, LE Sucar
International Journal of Approximate Reasoning 54 (8), 956-977, 2013
262013
A Bayesian approach for learning and tracking switching, non-stationary opponents
P Hernandez-Leal, B Rosman, ME Taylor, LE Sucar, E Munoz de Cote
Proceedings of the 2016 international conference on autonomous agents …, 2016
252016
An exploration strategy for non-stationary opponents
P Hernandez-Leal, Y Zhan, ME Taylor, LE Sucar, E Munoz de Cote
Autonomous Agents and Multi-Agent Systems 31, 971-1002, 2017
232017
Skynet: A top deep rl agent in the inaugural pommerman team competition
C Gao, P Hernandez-Leal, B Kartal, ME Taylor
arXiv preprint arXiv:1905.01360, 2019
222019
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