Abstract:
:We propose a model of a learning agent whose interaction with the environment is governed by a simulation-based projection, which allows the agent to project itself into future situations before it takes real action. Projective simulation is based on a random walk through a network of clips, which are elementary patches of episodic memory. The network of clips changes dynamically, both due to new perceptual input and due to certain compositional principles of the simulation process. During simulation, the clips are screened for specific features which trigger factual action of the agent. The scheme is different from other, computational, notions of simulation, and it provides a new element in an embodied cognitive science approach to intelligent action and learning. Our model provides a natural route for generalization to quantum-mechanical operation and connects the fields of reinforcement learning and quantum computation.
journal_name
Sci Repjournal_title
Scientific reportsauthors
Briegel HJ,De las Cuevas Gdoi
10.1038/srep00400subject
Has Abstractpub_date
2012-01-01 00:00:00pages
400issn
2045-2322journal_volume
2pub_type
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