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Found 4 papers, 1 papers with code
Translating Natural Language to Planning Goals with Large-Language Models
Recent large language models (LLMs) have demonstrated remarkable performance on a variety of natural language processing (NLP) tasks, leading to intense excitement about their applicability across various domains.
Order Matters: Generating Progressive Explanations for Planning Tasks in Human-Robot Teaming
Given this sequential process, a formulation based on goal-based MDP for generating progressive explanations is presented.
Online Explanation Generation for Human-Robot Teaming
The new explanation generation methods are based on a model reconciliation setting introduced in our prior work.
Correlated Equilibria for Approximate Variational Inference in MRFs
Almost all of the work in graphical models for game theory has mirrored previous work in probabilistic graphical models.
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