concept
active
concept:sequential-policiesSequential Policies
In active inference, a policy is a sequence of actions through time, as opposed to state-action mappings in RL.
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Frameworks (1)
framework
- Active Inferenceassociated_withFoundational framework by Karl Friston; the paper extends it to three hierarchical levels for modeling meta-awareness.
Related by similarity (8)
cosine ≥ 0.65 · no typed edgeEntities in the same semantic neighborhood but without a typed relation to this one — candidates for new edges or unrecognized duplicates.
- Sequence of actions considered by the agent; basis for planning.
- A geometric structure characterizing sequential reasoning task representations, used as a test case for manifold steering
- Language model reasoning tasks with sequential geometry used in experiments.
- Choosing sequences of actions based on expected free energy; prior probability of policy is softmax of expected free energy
- A formal language for describing concurrent processes via message passing.
- In reinforcement learning, a policy maps states to actions, specifying behavior at each state.
- RL algorithm used for training models to comply with the conflicting objective
- Policies assigned probability via softmax of expected free energy; enables self-evidencing behavior.