Sharing the Cost of Success: A Game for Evaluating and Learning Collaborative Multi-Agent Instruction Giving and Following Policies

• URL: http://arxiv.org/abs/2403.17497v1
• Date: Tue, 26 Mar 2024 08:58:28 GMT
• Title: Sharing the Cost of Success: A Game for Evaluating and Learning Collaborative Multi-Agent Instruction Giving and Following Policies
• Authors: Philipp Sadler, Sherzod Hakimov, David Schlangen,
• Abstract summary: We propose a challenging interactive reference game that requires two players to coordinate on vision and language observations. We show that a standard Proximal Policy Optimization (PPO) setup achieves a high success rate when bootstrapped with partner behaviors. We find that a pairing of neural partners indeed reduces the measured joint effort when playing together repeatedly.
• Score: 19.82683688911297
• License: http://creativecommons.org/licenses/by-sa/4.0/
• Abstract: In collaborative goal-oriented settings, the participants are not only interested in achieving a successful outcome, but do also implicitly negotiate the effort they put into the interaction (by adapting to each other). In this work, we propose a challenging interactive reference game that requires two players to coordinate on vision and language observations. The learning signal in this game is a score (given after playing) that takes into account the achieved goal and the players' assumed efforts during the interaction. We show that a standard Proximal Policy Optimization (PPO) setup achieves a high success rate when bootstrapped with heuristic partner behaviors that implement insights from the analysis of human-human interactions. And we find that a pairing of neural partners indeed reduces the measured joint effort when playing together repeatedly. However, we observe that in comparison to a reasonable heuristic pairing there is still room for improvement -- which invites further research in the direction of cost-sharing in collaborative interactions.

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