Exploring Shard-like Behavior: Empirical Insights into Contextual Decision-Making in RL Agents
Image generated by Microsoft Bing Image Creator Abstract Shard Theory posits that reinforcement learning agents can be modeled as collections of contextually activated decision influences, or "shards." However, the mechanistic definition of shards remains an open question. This study investigates the contextual activation claim of Shard Theory using a maze-solving...