18 results with keyword: 'decentralised monte carlo tree search for active perception'
The algorithm cycles between three phases (Alg. 1): 1) grow a search tree using MCTS, while taking into account information about the other robots, 2) update the
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Using this simulation strategy the MCTS program plays at the same level as the αβ program MIA, the best LOA playing entity in the world.. 3.5.3 Deterministic
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In this article we introduce a new MCTS variant, called MCTS-Solver, which has been designed to prove the game-theoretical value of a node in a search tree.. This is an important
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Key words: artificial intelligence (AI), search, planning, machine learning, Monte Carlo tree search (MCTS), reinforcement learning, temporal-difference (TD) learning, upper
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Long-term robot motion planning for active sound source localization with Monte Carlo tree search.. Quan Nguyen Van, Francis Colas, Emmanuel Vincent,
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We improve the performance of our player in the early game with an opening book computed through self play.. To assess the performance of our heuristics, we have performed a number
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The effects of strategy fusion can manifest in different ways. First, strategy fusion may arise since a deterministic solver may make different decisions in each of the states within
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The main contribution of the paper is the Mosaic AutoML platform, adapting and extend- ing the Monte-Carlo Tree Search setting to tackle the structured optimization problem of
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As the number of MCTS iterations in- creases, the memory usage of the algorithm is bounded only by the (combinatorially large) size of the game tree.. Sev- eral methods have
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This require- ment was behind the problem statement of the thesis: “How do we design a structured pattern- based parallel programming approach for efficient parallelism of MCTS for
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The HPLC method developed is sensitive and specific for the quantitative determination of Atenolol and Hydrochlorothiazide. Also the method is validated for
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MO-MCTS is tested, in comparison with a single-objective MCTS algorithm and a rolling horizon NSGA-II, in two different real-time games, the Deep Sea Treasure (DST) and
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20.01.2015 | Fachbereich Informatik | DKE: Seminar zu maschinellem Lernen | Robert Pinsler | 7!. Finding an
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This error appears on the Initiator/Responder when Main Mode or Aggressive Mode is used and, on the Initiator, the “Remote ID” on Tunnel configuration, doesn’t match with the
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The tree representing the problem solved by MCTS can be described as a rein- forcement learning problem with the following correspondence: states ∼ nodes of the tree, actions ∼
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Monte Carlo tree search (MCTS) is a probabilistic algorithm that uses lightweight random simulations to selectively grow a game tree.. MCTS has experienced a lot of success in do-
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