Record cause-effect feature-to-feature transitions

[brohrer]

In a structure mimicking human long term declarative memory, implement cause-effect transitions, each with a single feature cause and a single feature effect. Each also has an expected reward associated with it. The transitions are learned based on current and recent feature activities. The expected reward is learned based on current and near future rewards.

Each transition will also have a priming value associated with it. Priming serves both as a prediction and a planning mechanism. The priming will be a function of current and recent feature activities.

[brohrer]

I've done just enough visualization on this to provisionally mark it as complete.