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S2S - A Package for Computer-aided Matching of Entrants in Chess Tournaments

Nicolae Zsifkov, Lascu Mircea
1989 ICGA Journal  
Two important classes of algorithms for searching game trees are investigated: the minimal-window search algorithms, which examine the tree in a predetermined order, and the state-space search algorithms  ...  This book deals with algorithms for a special kind of decision trees: the game trees.  ...  Two important classes of algorithms for searching game trees are investigated: the minimal-window search algorithms, which examine the tree in a predetermined order, and the state-space search algorithms  ... 
doi:10.3233/icg-1989-12313 fatcat:u3vwzz4wivcczgnaff33wqbt6u

Tree Search vs Optimization Approaches for Map Generation [article]

Debosmita Bhaumik, Ahmed Khalifa, Michael Cerny Green, Julian Togelius
2020 arXiv   pre-print
Search-based procedural content generation uses stochastic global optimization algorithms to search for game content.  ...  We find that in general, optimization algorithms clearly outperform tree search algorithms, but given the right problem representation certain tree search algorithms perform similarly to optimization algorithms  ...  Acknowledgements Ahmed Khalifa acknowledges the financial support from NSF grant (Award number 1717324 -"RI: Small: General Intelligence through Algorithm Invention and Selection.").  ... 
arXiv:1903.11678v3 fatcat:xqbs2gfsurceteha255zz57c3q

Tree Search versus Optimization Approaches for Map Generation

Debosmita Bhaumik, Ahmed Khalifa, Michael Cerny Green, Julian Togelius
2020 Artificial Intelligence and Interactive Digital Entertainment Conference  
Search-based procedural content generation uses stochastic global optimization algorithms to search for game content.  ...  We find that in general, optimization algorithms clearly outperform tree search algorithms, but given the right problem representation certain tree search algorithms performs similarly to optimization  ...  Acknowledgements Ahmed Khalifa acknowledges the financial support from NSF grant (Award number 1717324 -"RI: Small: General Intelligence through Algorithm Invention and Selection.").  ... 
dblp:conf/aiide/BhaumikKGT20 fatcat:nekczbguonfbha7wwleet6dioe

Elastic Monte Carlo Tree Search with State Abstraction for Strategy Game Playing [article]

Linjie Xu, Jorge Hurtado-Grueso, Dominic Jeurissen, Diego Perez Liebana, Alexander Dockhorn
2022 arXiv   pre-print
Strategy video games challenge AI agents with their combinatorial search space caused by complex game elements. State abstraction is a popular technique that reduces the state space complexity.  ...  The elastic changes benefit from efficient searching brought by state abstraction but avoid the negative influence of using state abstraction for the whole search.  ...  Game state and action abstraction [4] are efficient techniques that reduce the search space for search-based methods.  ... 
arXiv:2205.15126v1 fatcat:e4ulu6bagzfhtlgay4pkdodzgm

Quantum Walk Algorithm to Compute Subgame Perfect Equilibrium in Finite Two-player Sequential Games

Arish Pitchai, A V Reddy, Nickolas Savarimuthu
2016 International Journal of Mathematical Sciences and Computing  
A fullwidth game tree of average branching factor b and height h has () h n O b  nodes in it. The proposed algorithm uses ( / ) O n b oracle queries to backtrack to the solution.  ...  Computational complexity of classical approaches to compute SGPE grows exponentially with the increase in height of the game tree.  ...  Even though Zermelo's algorithm is known to solve game tree of size n with O(n) queries, the number of queries is enormous for large game trees.  ... 
doi:10.5815/ijmsc.2016.03.03 fatcat:rfkqaeeervbv3kaeqcio3gncyu

A Survey on Minimax Trees and Associated Algorithms

Claude G. Diderich, Marc Gengler
1994 ICGA Journal  
the search space.  ...  The last part of this paper tries to give a succinct view on the state of the art in parallel minimax game tree searching.  ...  The last part of this paper tries to give a succinct view on the state of the art in parallel minimax game tree searching.  ... 
doi:10.3233/icg-1994-17413 fatcat:fcvdjsyqnbevdkdzkpapooyvl4

Agent Searching in a Tree and the Optimality of Iterative Deepening

P. Dasgupta, P.P. Chakrabarti, S.C. DeSarkar
1994 ICGA Journal  
the search space.  ...  The last part of this paper tries to give a succinct view on the state of the art in parallel minimax game tree searching.  ...  The last part of this paper tries to give a succinct view on the state of the art in parallel minimax game tree searching.  ... 
doi:10.3233/icg-1994-17411 fatcat:dymmynsy4ffdbphuppuyr2yida

A Bibliography on Minimax Trees

Claude G. Diderich
1994 ICGA Journal  
the search space.  ...  The last part of this paper tries to give a succinct view on the state of the art in parallel minimax game tree searching.  ...  The last part of this paper tries to give a succinct view on the state of the art in parallel minimax game tree searching.  ... 
doi:10.3233/icg-1994-17412 fatcat:awq5iq7wbne2tmz74bchpaj2q4

Dual Monte Carlo Tree Search [article]

Prashank Kadam, Ruiyang Xu, Karl Lieberherr
2021 arXiv   pre-print
Dual MCTS uses two different search trees, a single deep neural network, and a new update technique for the search trees using a combination of the PUCB, a sliding-window, and the epsilon-greedy algorithm  ...  The neural MCTS algorithm has been successful in finding near-optimal strategies for games through self-play.  ...  We claim that our algorithm performs better as the state space of the game increase.  ... 
arXiv:2103.11517v2 fatcat:qccwe2tiejdezm4d4itd4zrf7y

Efficient Exploration via First-Person Behavior Cloning Assisted Rapidly-Exploring Random Trees [article]

Max Zuo and Logan Schick and Matthew Gombolay and Nakul Gopalan
2022 arXiv   pre-print
Modern day computer games have extremely large state and action spaces.  ...  In this work we attempt to combine a human-tester's expertise in solving games, and the RRT's exhaustiveness to search a game's state space efficiently with high coverage.  ...  Aghyad and Moataz [1] explore a wide breadth of these methods, including evolutionary algorithms, genetic algorithms, and graph search algorithms for searching game state spaces.  ... 
arXiv:2203.12774v2 fatcat:dzhvvj62rraq3ksdyoac5y4vti

Online Evolution for Multi-action Adversarial Games [chapter]

Niels Justesen, Tobias Mahlmann, Julian Togelius
2016 Lecture Notes in Computer Science  
We implement Online Evolution for the turn-based multi-action game Hero Academy and compare it with a standard Monte Carlo Tree Search implementation as well as two types of greedy algorithms.  ...  In Online Evolution, an evolutionary algorithm is used to evolve the combination of atomic actions that make up a single move, with a state evaluation function used for fitness.  ...  Introduction Game-playing can fruitfully be seen as search: the search in the space of game states for desirable states which are reachable from the present state.  ... 
doi:10.1007/978-3-319-31204-0_38 fatcat:7vem2h33zngmtgbgvalolybthm

Beyond Intra-modality: A Survey of Heterogeneous Person Re-identification

Zheng Wang, Zhixiang Wang, Yinqiang Zheng, Yang Wu, Wenjun Zeng, Shin'ichi Satoh
2020 Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence  
Then, we describe and compare existing datasets for performing evaluations, and survey the models that have been widely employed in Hetero-ReID.  ...  In this paper, we provide a comprehensive review of state-of-the-art Hetero-ReID methods that address the challenge of inter-modality discrepancies.  ...  Acknowledgements The author thanks Rubens Moraes for discussions about this research and the reviewers for their suggestions.  ... 
doi:10.24963/ijcai.2020/681 dblp:conf/ijcai/Lelis20 fatcat:wiiqnkothrg7peauvaqspzap4y

Monte-Carlo Tree Search and minimax hybrids

Hendrik Baier, Mark H. M. Winands
2013 2013 IEEE Conference on Computational Inteligence in Games (CIG)  
Monte-Carlo Tree Search is a sampling-based search algorithm that has been successfully applied to a variety of games.  ...  However, MCTS builds a highly selective tree and can therefore miss crucial moves and fall into traps in tactical situations. Full-width minimax search does not suffer from this weakness.  ...  ACKNOWLEDGMENT This work is funded by the Netherlands Organisation for Scientific Research (NWO) in the framework of the project Go4Nature, grant number 612.000.938.  ... 
doi:10.1109/cig.2013.6633630 dblp:conf/cig/BaierW13 fatcat:ecs6tlykmvbsrjnfifeiq45vne

Open Loop Search for General Video Game Playing

Diego Perez Liebana, Jens Dieskau, Martin Hunermund, Sanaz Mostaghim, Simon Lucas
2015 Proceedings of the 2015 on Genetic and Evolutionary Computation Conference - GECCO '15  
Then, a tree search algorithm with a multi-armed bandit based tree policy is presented, followed by a Rolling Horizon Evolutionary Algorithm (RHEA) approach.  ...  This paper introduces three different open loop techniques for dealing with this problem. First, a simple directed depth first search algorithm is employed as a baseline.  ...  A tree search algorithm builds a game tree with game states as nodes and actions as edges, with the current game state as the root of the tree.  ... 
doi:10.1145/2739480.2754811 dblp:conf/gecco/LiebanaDHML15 fatcat:fc7rxqarlzfj7pyubphrl4gsgq

Monte Carlo Tree Search with Scalable Simulation Periods for Continuously Running Tasks [article]

Seydou Ba, Takuya Hiraoka, Takashi Onishi, Toru Nakata, Yoshimasa Tsuruoka
2018 arXiv   pre-print
Monte Carlo Tree Search (MCTS) is particularly adapted to domains where the potential actions can be represented as a tree of sequential decisions.  ...  For an effective action selection, MCTS performs many simulations to build a reliable tree representation of the decision space.  ...  The driving idea of MCTS is to determine the best action to take in the current state by representing the decision space with an incrementally growing search tree.  ... 
arXiv:1809.02378v1 fatcat:rvgm44l76zcb5ocugazf6ihpum
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