arXiv Open Access 2022

Reinforcement Learning for ConnectX

Sheel Shah Shubham Gupta

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Abstrak

ConnectX is a two-player game that generalizes the popular game Connect 4. The objective is to get X coins across a row, column, or diagonal of an M x N board. The first player to do so wins the game. The parameters (M, N, X) are allowed to change in each game, making ConnectX a novel and challenging problem. In this paper, we present our work on the implementation and modification of various reinforcement learning algorithms to play ConnectX.

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cs.AI

Penulis (2)

Sheel Shah

Shubham Gupta

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Shah, S., Gupta, S. (2022). Reinforcement Learning for ConnectX. https://arxiv.org/abs/2210.08263

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Informasi Jurnal

Tahun Terbit: 2022
Bahasa: en
Sumber Database: arXiv
Akses: Open Access ✓