Continuous Arvand: Motion Planning with Monte Carlo Random Walks ¨ Weifeng Chen and Martin Muller Department of Computing Science University of Alberta {weifeng3,mmueller}@ualberta.ca

Source URL: webdocs.cs.ualberta.ca

• Statistics
• Applied mathematics
• Search algorithms
• Stochastic processes
• Motion planning
• Rapidly-exploring random tree
• Random walk
• Probabilistic roadmap
• Urban planning
• Theoretical computer science
• Robot control
• Geography of Asia

Monte Carlo Tree Search for Simulated Car Racing Jacob Fischer1 , Nikolaj Falsted1 , Mathias Vielwerth1 , Julian Togelius2 , and Sebastian Risi1 1 Center for Computer Games Research, IT University of Copenhagen, Denmark

Source URL: julian.togelius.com

Monte Carlo *-Minimax Search Marc Lanctot1 , Abdallah Saffidine2 , Joel Veness3 , Christopher Archibald3 , and Mark H.M. Winands1 1 Department of Knowledge Engineering, Maastricht University, Netherlands, {marc.lanctot,

Source URL: jveness.info

• Mathematics
• Applied mathematics
• Computer chess
• Game theory
• Combinatorial game theory
• Minimax
• Alpha-beta pruning
• Negamax
• Expectiminimax tree
• Game artificial intelligence
• Artificial intelligence
• Search algorithms

The Monte-Carlo Approach in Amazons Julien Kloetzer1 , Hiroyuki Iida1 , and Bruno Bouzy2 1 Research Unit for Computers and Games Japan Advanced Institute of Science and Technology

Source URL: www.math-info.univ-paris5.fr

• Game artificial intelligence
• Abstract strategy games
• Combinatorial game theory
• Search algorithms
• Computer chess
• Game of the Amazons
• Minimax
• Monte Carlo method
• Game tree
• Mathematics
• Games
• Applied mathematics

IEEE TRANSACTIONS ON COMPUTATIONAL INTELLIGENCE AND AI IN GAMES, VOL. 4, NO. 1, MARCHA Survey of Monte Carlo Tree Search Methods Cameron Browne, Member, IEEE, Edward Powley, Member, IEEE, Daniel Whitehouse, Memb

Source URL: www.doc.ic.ac.uk

• Graph theory
• Search algorithms
• Game theory
• Computer chess
• Combinatorial game theory
• Minimax
• Reinforcement learning
• Expectiminimax tree
• Negamax
• Mathematics
• Game artificial intelligence
• Artificial intelligence

Jean-Noel Vittaut General Game Playing We present an adaptive method that enables a General Game Player using Monte-Carlo Tree Search to adapt its use of RAVE to the game it plays. This adaptation is done with a compari

Source URL: www.ai.univ-paris8.fr

Journal of Artificial Intelligence Research883 Submitted 06/13; publishedScalable and Efficient Bayes-Adaptive Reinforcement Learning Based on Monte-Carlo Tree Search

Source URL: www.gatsby.ucl.ac.uk

• Markov models
• Dynamic programming
• Markov processes
• Stochastic control
• Reinforcement learning
• Markov decision process
• Monte Carlo method
• Markov chain Monte Carlo
• Graphical model
• Statistics
• Probability and statistics
• Bayesian statistics

Monte Carlo Tree Search Cameron Browne Computational Creativity Group Imperial College London March 2012

Source URL: ccg.doc.gold.ac.uk

• Search algorithms
• Abstract strategy games
• Board games
• Computer chess
• Computer Go
• Minimax
• Morpion solitaire
• Alpha-beta pruning
• Monte Carlo method
• Games
• Mathematics
• Game artificial intelligence

Monte Carlo Tree Search with Bayesian Model Averaging for the Game of Go John Jeong You

Source URL: users.cecs.anu.edu.au

• Theoretical computer science
• Milwaukee County Transit System
• Computer Go
• Graphical model
• Transport
• Mathematics
• Applied mathematics
• Bayesian statistics
• Algorithm
• Mathematical logic

Variance Reduction in Monte-Carlo Tree Search Joel Veness University of Alberta Marc Lanctot University of Alberta

Source URL: webdocs.cs.ualberta.ca

• Randomness
• Variance reduction
• Computational statistics
• Antithetic variates
• Algebra of random variables
• Control variates
• Variance
• Normal distribution
• Random variate
• Statistics
• Probability and statistics
• Monte Carlo methods