Related papers: Collaborative Problem-Solving in an Optimization Game

Collaborative Problem-Solving in an Optimization Game

URL: http://arxiv.org/abs/2505.15490v1
Date: Wed, 21 May 2025 13:15:35 GMT
Title: Collaborative Problem-Solving in an Optimization Game
Authors: Isidora Jeknic, Alex Duchnowski, Alexander Koller,
Abstract summary: We introduce a novel dialogue game in which the agents collaboratively solve a two-player Traveling Salesman problem.<n>Our best agent solves 45% of games optimally in self-play.<n>It also demonstrates an ability to collaborate successfully with human users and generalize to unfamiliar graphs.
Score: 52.005042190810116
License: http://creativecommons.org/licenses/by/4.0/
Abstract: Dialogue agents that support human users in solving complex tasks have received much attention recently. Many such tasks are NP-hard optimization problems that require careful collaborative exploration of the solution space. We introduce a novel dialogue game in which the agents collaboratively solve a two-player Traveling Salesman problem, along with an agent that combines LLM prompting with symbolic mechanisms for state tracking and grounding. Our best agent solves 45% of games optimally in self-play. It also demonstrates an ability to collaborate successfully with human users and generalize to unfamiliar graphs.

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