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University of Manchester

Hex Board Game AI

Monte Carlo Tree Search Agent for the Hex Strategy Game

PythonMonte Carlo Tree SearchGame Theory

Built for the University of Manchester AI module. Hex is a two-player connection game on an 11×11 rhombus grid where the first player to form an unbroken chain across the board wins. The challenge is that Hex has no draws and is PSPACE-complete, making brute-force search infeasible.

The Problem

Classical minimax search is impractical for Hex due to the enormous branching factor and absence of a reliable heuristic evaluation function for intermediate positions.

The Approach

Implemented Monte Carlo Tree Search (MCTS) with a tuned exploration constant to balance exploration and exploitation within a fixed time budget per move. Adjusted simulation rollout policy and tree expansion strategy iteratively. Used virtual connections to guide rollout bias toward promising bridge formations.

The Outcome

Submitted a working MCTS agent to the COMP34111 tournament, competing correctly against all other student groups within the fixed time budget per move. A solid first encounter with adversarial tree search in a provably hard combinatorial game.

Hex Board Game AI