inverse decision modeling: learning interpretable representations of behavior
(PDF) Inverse Decision Modeling: Learning Interpretable.. Finally, given observed behavior , the composition of F and G gives its projection onto the space of behaviors that are parameterizable by (Definition 4): This is the inverse.
(PDF) Inverse Decision Modeling: Learning Interpretable. from i1.rgstatic.net
This paper develops an expressive, unifying perspective on inverse decision modeling: a framework for learning parameterized representations of sequential decision behavior,.
Virtual Site ICML
Decision analysis deals with modeling and enhancing decision processes. A principal challenge in improving behavior is in obtaining a transparent description of existing behavior in the first.
Inverse Contextual Bandits: Learning How Behavior Evolves over.
First, we model the evolving behavior of decision-makers in terms of contextual bandits, and formalize the problem of Inverse Contextual Bandits ("ICB"). Second, we propose two.
ICML 2021
Decision analysis deals with modeling and enhancing decision processes. A principal challenge in improving behavior is in obtaining a transparent description of existing behavior in the first.
