The basic concept is dynamic programming. It does have shortcomings as the size of the board becomes larger. But it works fine if you are not specifically interested in extreme large boards. Please see my blog post at leimao.github.io/project/Chomp-AI/. Thank you for your interest. You are the first person ever commented on my naive projects.
Did you use neuronal networks or just an algorithm, if you used an algorithm, could you tell me which one you used please ?
Nice AI! I'm pretty sure you would have won if you made the move from (7,5,2) to (5,5,2) since (5,5,2) is a losing state.
nevermind, that doesn't work
Any chance i could have a look on the AI strategy? Busy writing an AI for chomp myself but different perspectives would be useful!
The basic concept is dynamic programming. It does have shortcomings as the size of the board becomes larger. But it works fine if you are not specifically interested in extreme large boards. Please see my blog post at leimao.github.io/project/Chomp-AI/. Thank you for your interest. You are the first person ever commented on my naive projects.