In this paper we introduce CMAB-based search algorithms that use action abstraction schemes to reduce the action space considered during search. One of the approaches we introduce use regular action abstractions
Note that, in addition to the above algorithms and estimators, Open Bandit Pipeline provides flexible interfaces. Therefore, researchers can easily implement their own algorithms or estimators and evaluate them with our data and pipeline. Moreover, Open Bandit Pipeline provides an interface for ...
Bandit Algorithms for Tree Search Bandit based methods for tree search have recently gained popularity whenapplied to huge trees, e.g. in the game of go (Gelly et al., 2006). The UCTalgorit... R Munos - 《Computer Science》 被引量: 217发表: 2007年 ...
Xu et al. [15] propose a novel hierarchical data aggregation method using compressive sensing which combines a hierarchical network configuration. Their key idea is to set multiple compression thresholds adaptively based on cluster sizes at different levels of the data aggregation tree to optimize the...
Takuma Toyoda and Yoshiyuki Kotani suggested the idea of using previous simulated game results to improve the performance of the original Monte-Carlo Go program [13], and their work announced positive results on the larger Go board. In Tetris, Bohm et al. used genetic algorithms for the heurist...
2, Blackwellalso showsthat,providedthemaximumtotalexpectedrewardis boundedover all initialstates,equationsoftheform(13) maybe solvedeitherbyone ofthepolicyimprove- mentalgorithmsavailable for the purpose,or by startingwithan approximatefunction, substitutinign the right-handside and thusobtaininga second ...
We applied the proposed algorithm to synthetic problems and molecular-design demonstrations using a Monte Carlo tree search. According to the results, the proposed algorithm stably outperformed other bandit algorithms in the late stage of the search process, unless the optimal arm coincides in the ...
We consider the validation of randomly generated patterns in a Monte-Carlo Tree Search program. Our bandit-based genetic programming (BGP) algorithm, with proved mathematical properties, outperformed a highly optimized handcrafted module of a well-known computer-Go program with several world records ...
Takuma Toyoda and Yoshiyuki Kotani suggested the idea of using previous simulated game results to improve the performance of the original Monte-Carlo Go program [13], and their work announced positive results on the larger Go board. In Tetris, Bohm et al. used genetic algorithms for the heurist...
Algorithms developed for solv- ing RL problems, such as policy gradient methods, can be adapted for contextual bandit problems [16]. Currently, many efforts have been devoted to dealing with sequential decision-making problems using bandit-based approaches, where the decision maker seeks to select ...