1 citations · 1 across the 4 of their papers we have counts for
4 papers
A Tractable Continuous-Time Model for Designing Interventions for Time-Inconsistent Agents
Yasunori Akagi, Hideaki Kim, Daichi Fushihara +3
Designing effective goals and rewards for time-inconsistent agents is a central problem in many long-term tasks, such as learning, exercise, work, and project completion. An agent…
Psychological Benefits and Costs of Diversifying Algorithmic Recourse
Tomu Tominaga, Naomi Yamashita, Takeshi Kurashima
Algorithmic recourse provides counterfactual action plans that help people overturn unfavorable AI decisions. While diverse recourse sets may improve transparency and motivation, t…
Delta Matters: An Analytically Tractable Model for - Discounting Agents
Yasunori Akagi, Takeshi Kurashima
Humans exhibit time-inconsistent behavior, in which planned actions diverge from executed actions. Understanding time inconsistency and designing appropriate interventions is a key…
Reassessing Evaluation Functions in Algorithmic Recourse: An Empirical Study from a Human-Centered Perspective
Tomu Tominaga, Naomi Yamashita, Takeshi Kurashima
In this study, we critically examine the foundational premise of algorithmic recourse - a process of generating counterfactual action plans (i.e., recourses) assisting individuals…