Clever Computers: Playing Tic-Tac-Toe

Habgood, Jacob; Overmars, Mark H.

doi:10.1007/978-1-4302-0159-5_13

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A Brute-force Algorithms In Depth-first Search1

The Traditional Negamax Tree Search Algorithm1

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2014

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Cited by 2 publications

(3 citation statements)

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“…1 there is a simulation of MiniMax search for TicTac-Toe game [8]. Every node has a value calculated by the evaluation function.…”

Section: A Brute-force Algorithms In Depth-first Searchmentioning

confidence: 99%

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A Comparative Study of Game Tree Searching Methods

Elnaggar¹,

Aziem²,

Gadallah³

et al. 2014

IJACSA

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Abstract-In this paper, a comprehensive survey on gaming tree searching methods that can use to find the best move in two players zero-sum computer games was introduced. The purpose of this paper is to discuss, compares and analyzes various sequential and parallel algorithms of gaming tree, including some enhancement for them. Furthermore, a number of open research areas and suggestions of future work in this field are mentioned.

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“…1 there is a simulation of MiniMax search for TicTac-Toe game [8]. Every node has a value calculated by the evaluation function.…”

Section: A Brute-force Algorithms In Depth-first Searchmentioning

confidence: 99%

“…An example of a game tree for Tic-TacToe game [8] is shown in Fig. 1 The figure shows the following:…”

mentioning

confidence: 99%

A Comparative Study of Game Tree Searching Methods

Elnaggar¹,

Aziem²,

Gadallah³

et al. 2014

IJACSA

View full text Add to dashboard Cite

show abstract

“…1 there is a simulation of MiniMax search for Tic-Tac-Toe game [13]. Every node has a value calculated by the evaluation function.…”

Section: The Traditional Negamax Tree Search Algorithmmentioning

confidence: 99%

Enhanced parallel NegaMax tree search algorithm on GPU

Elnaggar

Gadallah

Aziem

et al. 2014

2014 IEEE International Conference on Progress in Informatics and Computing

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Parallel performance for GPUs today surpasses the traditional multi-core CPUs. Currently, many researchers started to test several AI algorithms on GPUs instead of CPUs, especially after the release of libraries such as CUDA and OpenCL that allows the implementation of general algorithms on the GPU. One of the most famous game tree search algorithms is Negamax, which tries to find the optimal next move for zero sum games. In this research, an implementation of an enhanced parallel NegaMax algorithm is presented, that runs on GPU using CUDA library. The enhanced algorithms use techniques such as no divergence, dynamic parallelism and shared GPU table. The approach was tested in checkers and chess games. It was compared with previous studies, including threads on CPU for up to 6x speedup for an 8 core processor and threads on GPU using iterative dependence and fixed grid and block size for up to 40x speedup at 14 depth. Furthermore, the approach was tested with different depths on the CPU and the GPU. The result shows speed up for parallel GPU up to 80x at 14 depth for checkers game and 90x at 14 depth for chess game, which doubled the previous research results.

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Clever Computers: Playing Tic-Tac-Toe

Cited by 2 publications

References 0 publications

A Comparative Study of Game Tree Searching Methods

A Comparative Study of Game Tree Searching Methods

Enhanced parallel NegaMax tree search algorithm on GPU

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