8 citations · 18 across the 10 of their papers we have counts for
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cs.HC2024
Aligning Judgment Using Task Context and Explanations to Improve Human-Recommender System Performance
Divya Srivastava, Karen M. Feigh
Recommender systems, while a powerful decision making tool, are often operationalized as black box models, such that their AI algorithms are not accessible or interpretable by huma…
cs.RO2024
LTL-D*: Incrementally Optimal Replanning for Feasible and Infeasible Tasks in Linear Temporal Logic Specifications
Jiming Ren, Haris Miller, Karen M. Feigh +2
This paper presents an incremental replanning algorithm, dubbed LTL-D*, for temporal-logic-based task planning in a dynamically changing environment. Unexpected changes in the envi…
cs.RO2024★ 3 cited
Inferring Belief States in Partially-Observable Human-Robot Teams
Jack Kolb, Karen M. Feigh
We investigate the real-time estimation of human situation awareness using observations from a robot teammate with limited visibility. In human factors and human-autonomy teaming,…