53 citations · 178 across the 12 of their papers we have counts for
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cs.AI2022
Relative Behavioral Attributes: Filling the Gap between Symbolic Goal Specification and Reward Learning from Human Preferences
Lin Guan, Karthik Valmeekam, Subbarao Kambhampati
Generating complex behaviors that satisfy the preferences of non-expert users is a crucial requirement for AI agents. Interactive reward learning from trajectory comparisons (a.k.a…
cs.CL2022★ 50 cited
PlanBench: An Extensible Benchmark for Evaluating Large Language Models on Planning and Reasoning about Change
Karthik Valmeekam, Matthew Marquez, Alberto Olmo +2
Generating plans of action, and reasoning about change have long been considered a core competence of intelligent agents. It is thus no surprise that evaluating the planning and re…