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A policy is a plan of action for tackling political issues. It is often initated by a political party in government, which undergoes reforms and changes by interested actors (for example, opposition parties and lobby groups).


In AI planning and reinforcement learning, a policy prescribes a non-empty deliberation (sequence of actions) given a non-empty sequence of states.


Types of policy include:

  • stationary (resp. non-stationary)
  • deterministic (resp. stochastic, randomized and sometimesnon-deterministic)
  • memoryless (E.g. non-stationary)
  • causal (resp. non-causal)
  • index
  • opportunistic (resp. non-opportunistic)

These qualifiers can be combined, so for example you could have a stationary-memoryless-index policy.

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This page was last modified 22:22, 14 Sep 2004.
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