arXiv AI
Oct 27

Efficient Generation of Diverse Cooperative Agents with World Models

The paper introduces XPM-WM, a framework that uses learned world models to generate simulated trajectories for Cross-play Minimization (XPM) in Zero-Shot Coordination. By replacing costly Mixed-Play sampling with model-generated data, XPM-WM improves sample efficiency and scales linearly with population size, producing diverse partner agents that match the performance of existing methods. The approach also bootstraps training for subsequent agents and can be extended to other population‑based training techniques.

By Yi Loo, Akshunn Trivedi, Malika Meghjani
arXiv AI
Jul 7

Multi-Robot Open Adaptive Teaming Across Unseen Environments, Partners, and Scales

arXiv:2607. 04972v1 Announce Type: cross Abstract: Deploying robot teams in the real world requires simultaneous adaptation to unseen environments, unknown partners, and varying team sizes, yet existing approaches often address these challenges in isolation under the closed-world assumption of fixed teammates.

By Yang Li, Feng Xue, Fan Mo, Yunhao Liu, Jianhong Wang, Ying Wen, Qingrui Zhang, Shaoshuai Mou, Wei Pan
arXiv AI
Sep 11

ROTATE: Regret-driven Open-ended Training for Ad Hoc Teamwork

The paper introduces ROTATE, a regret-driven open‑ended training framework that jointly improves an Ad Hoc Teamwork (AHT) agent and an adversarial teammate generator. Unlike traditional two‑stage pipelines, ROTATE alternates between enhancing the agent and generating teammates that specifically probe its collaboration weaknesses. Experiments on Overcooked and Level‑Based Foraging show that ROTATE outperforms existing baselines on unseen teammates, setting a new benchmark for robust, generalizable teamwork.

By Caroline Wang, Arrasy Rahman, Benjamin Nativi, Jiaxun Cui, Yoonchang Sung, Peter Stone
arXiv AI
Jun 17

Algorithmic Prompt Generation for Diverse Human-like Teaming and Communication with Large Language Models

arXiv:2504. 03991v2 Announce Type: replace-cross Abstract: Understanding how humans collaborate and communicate in teams is essential for improving human-agent teaming and AI-assisted decision-making.

By Siddharth Srikanth, Varun Bhatt, Boshen Zhang, Werner Hager, Charles Michael Lewis, Katia P. Sycara, Aaquib Tabrez, Stefanos Nikolaidis