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I have an idea where I want to build an ML system that generates different sets of board game rules (think tic-tac-toe type games), then trains models to play t
by Smergnus 4y ago
I have an idea where I want to build an ML system that generates different sets of board game rules (think tic-tac-toe type games), then trains models to play that game, and scores each set of rules based on a set of criteria. For example: no side should always win, the skill ceiling should be high (models should keep improving when trained more). A less skilled (trained) model should sometimes be able to beat a more skilled model. The games should end within a reasonable number of turns. Etc. The high level system should then generate new rulesets, searching for a ruleset that scores optimally on the criteria. Would Sematic be good for this?
- neutralino1 4y agoThanks for your question! Yes, Sematic has a neat feature that can help: Dynamic Graphs. Because Sematic uses simple Python to declare the control and data flow of your graph, you can simply loop over configurations (in your case different sets of board game rules) and train a model for each config, and eventually aggregate results to determine the winner. Join our Discord in you want to discuss this further – https://discord.gg/4KZJ6kYVax https://discord.gg/4KZJ6kYVax
- Smergnus 4y agoAwesome. Thanks!