AAMAS’21 camready: AIP loss bounds

Our AAMAS’21 paper on loss bounds for influence-based abstraction is online.

In this paper, we derive conditions for ‘approximate influence predictors’ to give small value-loss when used in small (abstracted) MDPs. From these conditions we conclude that that learning such AIPs with cross-entropy loss seems sensible.

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