Boltzmann State-Dependent Rationality
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Abstract (arXiv)
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.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 7 of its 16 references that are in the map. First posted on arXiv 26 Apr 2024.
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References · 7
- 2019On the Utility of Learning about Humans for Human-AI Coordinationcited by 349
- 2022Imitation Learning by Estimating Expertise of Demonstratorscited by 50
- 2021TRAIL: Near-Optimal Imitation Learning with Suboptimal Datacited by 39
- 2021On the Importance of Environments in Human-Robot Coordinationcited by 37
- 2022The Boltzmann Policy Distribution: Accounting for Systematic Suboptimality in Human Modelscited by 31
- 2018Multi-Task Trust Transfer for Human-Robot Interactioncited by 11
- 2021Show Me What You Can Do: Capability Calibration on Reachable Workspace for Human-Robot Collaborationcited by 4
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