shard theory: Nonlinear Function
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shard theory

This page is from my personal notes, and has not been specifically reviewed for public consumption. It might be incomplete, wrong, outdated, or stupid. Caveat lector.

Shard theory's basic ontology of RL holds that shards are contextually activated, behavior-steering computations in neural networks (biological and artificial). The circuits that implement a shard that garners reinforcement are reinforced, meaning that that shard will be more likely to trigger again in the future, when given similar cognitive inputs.

References:

My current vague impressions of shard theory: