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A Modified Memory-Based Reinforcement Learning Method for Solving POMDP ProblemsLEI ZHENG; CHO, Siu-Yeung.Neural processing letters. 2011, Vol 33, Num 2, pp 187-200, issn 1370-4621, 14 p.Article

An agent-based approach equipped with game theory: Strategic collaboration among learning agents during a dynamic market change in the California electricity crisisSUEYOSHI, Toshiyuki.Energy economics. 2010, Vol 32, Num 5, pp 1009-1024, issn 0140-9883, 16 p.Article

Reinforcement learning for discounted values often loses the goal in the application to animal learningYAMAGUCHI, Yoshiya; SAKAI, Yutaka.Neural networks. 2012, Vol 35, pp 88-91, issn 0893-6080, 4 p.Article

Situating visual searchNAKAYAMA, Ken; MARTINI, Paolo.Vision research (Oxford). 2011, Vol 51, Num 13, pp 1526-1537, issn 0042-6989, 12 p.Article

COllective INtelligence with sequences of actions: Coordinating actions in multi-agent systemsJAN'T HOEN, Pieter; BOHTE, Sander M.Report - Software engineering. 2003, Num 2, pp 1-11, issn 1386-369X, 11 p.Article

TD-Gammon, a self-teaching backgammon program, achieves master-lever playTESAURO, G.Neural computation. 1994, Vol 6, Num 2, pp 215-219, issn 0899-7667Article

Apprentissage par renforcement factorisé pour le comportement de personnages non joueurs = Learning factored MDPs in reinforcement learning for non player characters in video gamesDEGRIS, Thomas; SIGAUD, Olivier; WUILLEMIN, Pierre-Henri et al.Revue d'intelligence artificielle. 2009, Vol 23, Num 2-3, pp 221-251, issn 0992-499X, 31 p.Article

Construction d'un joueur artificiel pour Tetris = Building an artificial player for TetrisTHIERY, Christophe; SCHERRER, Bruno.Revue d'intelligence artificielle. 2009, Vol 23, Num 2-3, pp 387-407, issn 0992-499X, 21 p.Article

Adaptive game AI with dynamic scripting : Machine learning and gamesSPRONCK, Pieter; PONSEN, Marc; SPRINKHUIZEN-KUYPER, Ida et al.Machine learning. 2006, Vol 63, Num 3, pp 217-248, issn 0885-6125, 32 p.Article

DistanceRank : An intelligent ranking algorithm for web pagesALI MOHAMMAD ZAREH BIDOKI; YAZDANI, Nasser.Information processing & management. 2008, Vol 44, Num 2, pp 877-892, issn 0306-4573, 16 p.Article

Graph kernels and Gaussian processes for relational reinforcement learningDRIESSENS, Kurt; RAMON, Jan; GÄRTNER, Thomas et al.Machine learning. 2006, Vol 64, Num 1-3, pp 91-119, issn 0885-6125, 29 p.Conference Paper

Evidence for learning to learn behavior in normal form gamesSALMON, Timothy C.Theory and decision. 2004, Vol 56, Num 4, pp 367-404, issn 0040-5833, 38 p.Article

Dopamine Modulates Reward-Related VigorBEIERHOLM, Ulrik; GUITART-MASIP, Marc; ECONOMIDES, Marcos et al.Neuropsychopharmacology (New York, NY). 2013, Vol 38, Num 8, pp 1495-1503, issn 0893-133X, 9 p.Article

CHQ : A multi-agent reinforcement learning scheme for partially observable markov decision processesOSADA, Hiroshi; FUJITA, Satoshi.IEICE transactions on information and systems. 2005, Vol 88, Num 5, pp 1004-1011, issn 0916-8532, 8 p.Article

Subjective and model-estimated reward prediction: Association with the feedback-related negativity (FRN) and reward prediction error in a reinforcement learning taskICHIKAWA, Naho; SIEGLE, Greg J; DOMBROVSKI, Alexandre et al.International journal of psychophysiology. 2010, Vol 78, Num 3, pp 273-283, issn 0167-8760, 11 p.Article

Exploiting intelligence in fighting action games using neural networksCHO, Byeong Heon; JUNG, Sung Hoon; SEONG, Yeong Rak et al.IEICE transactions on information and systems. 2006, Vol 89, Num 3, pp 1249-1256, issn 0916-8532, 8 p.Article

The misbehavior of value and the discipline of the willDAYAN, Peter; NIV, Yael; SEYMOUR, Ben et al.Neural networks. 2006, Vol 19, Num 8, pp 1153-1160, issn 0893-6080, 8 p.Article

Navigating Complex Decision Spaces: Problems and Paradigms in Sequential ChoiceWALSH, Matthew M; ANDERSON, John R.Psychological bulletin. 2014, Vol 140, Num 2, pp 466-486, issn 0033-2909, 21 p.Article

The asymptotic equipartition property in reinforcement learning and its relation to return maximizationIWATA, Kazunori; IKEDA, Kazushi; SAKAI, Hideaki et al.Neural networks. 2006, Vol 19, Num 1, pp 62-75, issn 0893-6080, 14 p.Article

The first learning track of the international planning competitionFERN, Alan; KHARDON, Roni; TADEPALLI, Prasad et al.Machine learning. 2011, Vol 84, Num 1-2, pp 81-107, issn 0885-6125, 27 p.Article

Apprentissage par renforcement d'actes de communication dans un système multi-agent = Reinforcement learning of multi-agent communicative actsHOET, Shirley; SABOURET, Nicolas.Revue d'intelligence artificielle. 2010, Vol 24, Num 2, pp 159-188, issn 0992-499X, 30 p.Conference Paper

Reliability of internal prediction/estimation and its application. I. Adaptive action selection reflecting reliability of value functionSAKAGUCHI, Yutaka; TAKANO, Mitsuo.Neural networks. 2004, Vol 17, Num 7, pp 935-952, issn 0893-6080, 18 p.Article

The effect of novelty on reinforcement learningHOUILLON, A; LORENZ, R. C; BOEHMER, W et al.Decision making (neural and behavioural approaches). Progress in brain research. 2013, Vol 202, pp 415-439, issn 0079-6123, isbn 978-0-444-62604-2, 1Vol, 25 p.Book Chapter

Relativized hierarchical decomposition of Markov decision processesRAVINDRAN, B.Decision making (neural and behavioural approaches). Progress in brain research. 2013, Vol 202, pp 465-488, issn 0079-6123, isbn 978-0-444-62604-2, 1Vol, 24 p.Book Chapter

Hippocampal replay contributes to within session learning in a temporal difference reinforcement learning modelJOHNSON, Adam; REDISH, A. David.Neural networks. 2005, Vol 18, Num 9, pp 1163-1171, issn 0893-6080, 9 p.Article

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