Evolving Tic-Tac-Toe Playing Algorithms Using Co-Evolution, Interactive Fitness and Genetic Programming

Mohammadi, Helia; Browne, Nigel P. A.; Venetsanopoulos, A.N.; Santos, Maribel Yasmina

doi:10.7763/ijcte.2013.v5.799

Cited by 7 publications

(2 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Mohammadi (Mohammadi et al, 2013) proposed genetic programming, coevolution, and interactive fitness in purpose to develop a human-competitive algorithm for playing tic-tac-toe. The algorithm used a 3x3 matrix to represent the chromosome and evaluated by traditional GA operators such as selection, crossover, and mutation.…”

Section: Tic-tac-toementioning

confidence: 99%

Using Genetic Algorithm to Solve Puzzle Games: A Review

Bukhori,

Felix,

Ali

2024

CNAHPC

View full text Add to dashboard Cite

Puzzles have been recognized for their development as a popular form of entertainment due to their ability to intricately challenge the mind while engendering creativity in the player. The development of puzzle games has given rise to a new generation of puzzle games characterized by diverse sequences and different image variations. With the rapid development of puzzle games, we looked at solving approaches using Genetic Algorithms (GA). In this paper, we try to analyze several puzzle games such as Sliding Blocks, Sudoku, Tic-Tac-Toe, and Jigsaw that can be solved using GA. We found that 120 papers have examined the use of GA for puzzle games, and eliminated into 14 papers. We evaluated these 14 papers for each puzzle game we selected by comparing the chromosome representation, GA operator, GA parameters, and the results. Based on the discussion, the application of GA to solve puzzle games can be effectively executed with a high degree of accuracy. Puzzle games that use measurement methods such as Sliding Block, Sudoku, and Jigsaw run in a similar pattern. What is common to all of them is that the chromosomes are represented as matrices or arrays in all cases, and standard genetic operators such as selection, crossover, and mutation are used. The population size is large, often 1000 chromosomes, and parameters such as mutation rate are kept low, around 5%. On the other hand, the performance of GA for solving Tetris and Tic-Tac-Toe from each publication cannot be compared due to different measurement methods and metrics.

show abstract

Section: Tic-tac-toementioning

confidence: 99%

Using Genetic Algorithm to Solve Puzzle Games: A Review

Bukhori,

Felix,

Ali

2024

CNAHPC

View full text Add to dashboard Cite

show abstract

“…They succeeded in finding 72,657 such strategies, and also came to some other interesting conclusions, which verify our existing notions about the game. Mohammadi et al [43] presented a co‐evolution and interactive fitness‐based genetic algorithm to build a human‐competitive player. Ling et al [44] used a double transfer function and Rajani et al [45] applied the Hamming distance classifier, on neural networks to demonstrate the advantages of each method.…”

Section: Literature Reviewmentioning

confidence: 99%

Randomised fast no‐loss expert system to play tic‐tac‐toe like a human

Paul

2020

Cognitive Computation and Systems

View full text Add to dashboard Cite

This paper introduces a blazingly fast, no-loss expert system for Tic Tac Toe using Decision Trees called T3DT, that tries to emulate human gameplay as closely as possible. It does not make use of any brute force, minimax or evolutionary techniques, but is still always unbeatable. In order to make the gameplay more human-like, randomization is prioritized and T3DT randomly chooses one of the multiple optimal moves at each step. Since it does not need to analyse the complete game tree at any point, T3DT is exceptionally faster than any brute force or minimax algorithm, this has been shown theoretically as well as empirically from clock-time analyses in this paper. T3DT also doesn't need the data sets or the time to train an evolutionary model, making it a practical no-loss approach to play Tic Tac Toe.

show abstract