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Effective and efficient forgetting of learned knowledge in Soar's working and procedural memories
2013
Cognitive Systems Research
Effective management of learned knowledge is a challenge when modeling human-level behavior within complex, temporally extended tasks. This work evaluates one approach to this problem: forgetting knowledge that is not in active use (as determined by base-level activation) and can likely be reconstructed if it becomes relevant. We apply this model to the working and procedural memories of Soar. When evaluated in simulated, robotic exploration and a competitive, multi-player game, these policies
doi:10.1016/j.cogsys.2012.12.003
fatcat:nmtyvdjoqbepphqdf6pz665a3a