Counterfactual off-policy evaluation with gumbel-max structural causal models
We introduce an off-policy evaluation procedure for highlighting episodes where applying a reinforcement learned (RL) policy is likely to have produced a substantially different outcome than the observed policy. In particular, we introduce a class of structural causal models (SCMs) for generating co...
| Main Authors: | , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
MLResearch Press
2021
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| Online Access: | https://hdl.handle.net/1721.1/130437 |