Glossary · Meaning and specification
Cooperative inverse reinforcement learning (CIRL)
A cooperative partial-information game in which human and machine both pursue the human's reward but the machine is uncertain of it, so optimal play includes questions and teaching. Evaluation analogue: query where posterior uncertainty is high.
Also called: CIRL, cooperative inverse reinforcement learning
Defined in
Handbook · PracticeInverse evaluation designTreat expert accept/reject decisions as evidence about a latent judgment, and use the posterior to find criteria, thresholds and the questions worth asking.Related terms
- Inverse reinforcement learning (IRL)
- Infers which reward functions could explain observed behavior, often as a Bayesian posterior under a Boltzmann (noisily rational) choice model. Many rewards can explain the same behavior, so the inferred reward is only partly identifiable.