Tic-Tac Toe
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Software Architecture:
RL-Glue mechanism:
* "Environment" - Returns a 'state', set of valid actions and a reward.
* "Agent" - Returns an action
* Run on a common platform
* A sample invocation would be
./main.py 100 "OptimalAgent" "TicTacToe:random:RandomAgent"
this starts the TicTacToe with the Agent being the OptimalAgent, and the
opponent is a RandomAgent and is randomly chosen to start first;
* Another sample invocation would be
./main.py 100 "PolicyGradient" "TicTacToe:false:OptimalAgent"
This does the same, with the PolicyGradient as the Agent, and the
OptimalAgent as the opponent; though now the Agent always starts first.