Boltzmann State-Dependent Rationality
This work addresses the challenge of capturing structured irrationality in human decision-making models, but it appears incremental as it builds on existing Boltzmann rationality frameworks.
The paper tackles the problem of modeling human behavior by introducing a state-dependent suboptimality function in Boltzmann rationality models, which enhances expressivity while maintaining computational tractability. It presents limited preliminary results and outlines future research directions.
This paper expands on existing learned models of human behavior via a measured step in structured irrationality. Specifically, by replacing the suboptimality constant $β$ in a Boltzmann rationality model with a function over states $β(s)$, we gain natural expressivity in a computationally tractable manner. This paper discusses relevant mathematical theory, sets up several experimental designs, presents limited preliminary results, and proposes future investigations.