Projective simulation for artificial intelligence
- Agent learns based on memory 'clips' which are combined using some pseudo-bayesian method to trigger actions.
- These clips are learned from experience / observation.
- Quote: "..more complex behavior seems to arise when an agent is able to “think for a while†before it “decides what to do next.†This means the agent somehow evaluates a given situation in the light of previous experience, whereby the type of evaluation is different from the execution of a simple reflex circuit"
- Quote: "Learning is achieved by evaluating past experience, for example by simple reinforcement learning".
- The forward exploration of learned action-stimulus patterns is seemingly a general problem-solving strategy (my generalization).
- Pretty simple task:
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- Robot can only move left / right; shows a symbol to indicate which way it (might?) be going.
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