A basic minimax algorithm seems sufficient. There are some examples to take notes from:
- gorisanson/quoridor-ai: Quoridor AI based on Monte Carlo tree search
- MedeaMelana/quoridorai: Automatically exported from code.google.com/p/quoridorai
- Massagué Respall, Victor & Brown, Joseph & Aslam, Hamna. (2018). Monte Carlo Tree Search for Quoridor. This paper presents a preliminary study using Monte Carlo Tree Search (MCTS) on the board game Quoridor. Quoridor is an exciting game for the expansion of player agents in MCTS due to having a mechanically simple rule set. However, Quoridor has a state-space complexity similar to Chess with higher game-tree complexity. The system is shown to perform well against current existing methods, defeating a set of player agents drawn from an existing digital implementation as well as a previous strategy using a GA.