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General Sum Off-Belief Learning

run main.py for rl, obl or ot-rl. Run main_FSP.py for fictitious self play, the following options can be used for either (although some will not have any effect on FSP).

options

**--lvls** LEVELS

	Select number of OBL/OT_RL levels to run through, defaults to 10.

**--game** kuhn/leduc

	Choose either kuhn poker or leduc hold 'em.

**-ab, --avg_bel**

	Generate an averaged belief (over levels), and use this in OBL. 

**-ap, --avg_pol**

	Generate the averaged policy across levels and use this when evaluating.

**-al, --avg_learn**

	When carrying out OBL, use the opponent's averaged policy to find their action.

**-a, --all_avg**

	Averaged belief, policy and learning.

**--debug**

	Prints out debugging information.

**-v**

	Prints out some information about progress.

**--learner** LEARNER_CHOICE
	
	Choose learner from rl, ot_rl or obl, for learning uising obl. Defaults to obl	

**--fsp**

	Uses FSP to learn nash, obl is default.

**--obl**
	Uses obl/rl/ot_rl.

Example usage: python main.py -a -v --obl --lvls 5

Dependencies

Name

matplotlib

numpy

scipy

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