kulinshah98 / AI-Agent-Tic-Tac-Toe

A python implementation of an agent for ultimate tic-tac-toe using Monte Carlo Tree Search and Upper Confidential Bound

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AI-Agent-for-Ultimate-Tic-Tac-Toe

An AI agent implemented using Monte Carlo Tree Search (MCTS) using Upper Confidence Bounds (UCT).

Game Description

Resources for MCTS and UCT

Test

  • Participated in AI tournament(rules) in which total 90 teams participated. Qualified for semifinals along with 30 teams.
  • Semifinals had 3 pools each having 10 teams. Secured 5th rank in semifinals.

Scope of improvement

  • Backpropogation step of MCTS properly to store heuristic
  • Implementation in C++ instead of Python for more number of simulations
  • Evaluation function

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A python implementation of an agent for ultimate tic-tac-toe using Monte Carlo Tree Search and Upper Confidential Bound


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Language:Python 100.0%