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------------------------------------------- -------- Gomoku Adversarial Search -------- ------------------------------------------- ---------- Created By: --------- ---------- Chandler Severson --------- ---------- & --------- ---------- Janelle Bakey --------- ------------------------------------------- 1. General Information This program is an example of Adversarial Search techniques. Specifically MiniMax search with Alpha-Beta pruning. This program was designed specifically to work with the Gomoku server program that can be found here: https://github.com/wfi/gomoku. The server program is written in Racket and this program in Java. This project was made for CS455 - Artificial Intelligence, Southern Oregon University, Winter 2017. 2. Running the Program In order to start the program, first open the GomokuServer found in the link above, and then run GomokuClient like 'java GomokuClient'. After connecting, you can start this agent again to make it play against itself or use the ManualPlayer racket class to play against the agent. 3. Acknowledgements Information about Gomoku and the "threats" posed by moves was found here: https://www.mimuw.edu.pl/~awojna/SID/referaty/Go-Moku.pdf. The algorithms were implemented based on pseudocode in Artificial Intelligence, A Modern Approach - Third Edition (Russel & Norvig). 4. Other Ideas/Comments When implementing the Heuristic evaluation function, we overlooked a few things, causing some logic issues later in development. In addition, the actual move search runs quite slow, sometimes up to 5-10sec to find an optimal move. We won't be winning any tournaments with this one. (Feb 20, 2017: Our AI actually won the class tournament!!)
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A Gomoku-Playing AI. Using Minimax search with Alpha-Beta pruning.
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