This introduces a ProgressiveLearner class that tries to learn a useful heuristic from playing a game (and then bootstrapping).
More importantly, it also includes interfaces for IActionFeatureVector and IStateFeatureVector to enable game-specific action- or state-spaces to be defined, that can then hook into this auto-learning process.
IStateFeatureVector examples so far implemented for Dots and Boxes, Love Letter and Dominion (in increasing order of complexity). This is also a useful branching point for implementation of reinforcement learning.
This introduces a ProgressiveLearner class that tries to learn a useful heuristic from playing a game (and then bootstrapping).
More importantly, it also includes interfaces for IActionFeatureVector and IStateFeatureVector to enable game-specific action- or state-spaces to be defined, that can then hook into this auto-learning process.
IStateFeatureVector examples so far implemented for Dots and Boxes, Love Letter and Dominion (in increasing order of complexity). This is also a useful branching point for implementation of reinforcement learning.