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ICML
2010
IEEE

Modeling Interaction via the Principle of Maximum Causal Entropy

13 years 4 months ago
Modeling Interaction via the Principle of Maximum Causal Entropy
The principle of maximum entropy provides a powerful framework for statistical models of joint, conditional, and marginal distributions. However, there are many important distributions with elements of interaction and feedback where its applicability has not been established. This work presents the principle of maximum causal entropy--an approach based on causally conditioned probabilities that can appropriately model the availability and influence of sequentially revealed side information. Using this principle, we derive models for sequential data with revealed information, interaction, and feedback, and demonstrate their applicability for statistically framing inverse optimal control and decision prediction tasks.
Brian Ziebart, J. Andrew Bagnell, Anind K. Dey
Added 09 Nov 2010
Updated 09 Nov 2010
Type Conference
Year 2010
Where ICML
Authors Brian Ziebart, J. Andrew Bagnell, Anind K. Dey
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