Adaptive playouts for online learning of policies during Monte Carlo tree search

DOI10.1016/J.TCS.2016.06.029zbMath1370.68260OpenAlexW2468569233MaRDI QIDQ307776

Tobias Graf, Marco Platzner

Publication date: 5 September 2016

Published in: Theoretical Computer Science (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.tcs.2016.06.029

zbMATH Keywords

reinforcement learningcomputer GoMonte Carlo tree searchadaptive playouts

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Problem solving in the context of artificial intelligence (heuristics, search strategies, etc.) (68T20) Combinatorial games (91A46)

Uses Software

• PACHI

Cites Work

• Unnamed Item
• Simple statistical gradient-following algorithms for connectionist reinforcement learning
• Using deep convolutional neural networks in Monte Carlo tree search
• Efficiency of Static Knowledge Bias in Monte-Carlo Tree Search
• Investigating the Limits of Monte-Carlo Tree Search Methods in Computer Go
• Monte-Carlo Simulation Balancing in Practice
• Algorithms for Reinforcement Learning
• PROGRESSIVE STRATEGIES FOR MONTE-CARLO TREE SEARCH

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