JaxAHT: A JAX-Based Library for Ad Hoc Teamwork

arXiv:2609.13716 · cs.AI · Submitted 2026-09-12 · Read on arXiv

cs.AI

Submitted: 2026-09-12

Updated: 2026-10-11

Code: https://github.com/ax-ml/jax

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Ad Hoc Teamwork — 2× in this paper · explained in 1 episode
• Benchmark — 2× in this paper · explained in 2 episodes
• Unified Framework — 1× in this paper · explained in 5 episodes

Sources

• Melting Pot 2.0
• Human-compatible driving partners through data-regularized self-play reinforcement learning
• Is Independent Learning All You Need in the StarCraft Multi-Agent Challenge?
• Proximal Policy Optimization Algorithms
• Evaluating and Modelling Hanabi-Playing Agents
• ROTATE: Regret-driven Open-ended Training for Ad Hoc Teamwork
• A Survey of Progress on Cooperative Multi-agent Reinforcement Learning in Open Environment

Related papers

• MAVEN-T: Reinforced Heterogeneous Distillation for Real-Time Multi-Agent Trajectory Prediction
• Model Discovery Agent: LLM-assisted Bayesian experiment design for data-efficient discovery of mechanistic world models
• Agents' Last Exam
• The Clinician's Veto: Navigating Trust, Liability, and Uncertainty in Autonomous AI Prescribing
• MindHelper: Closed-Loop Embodied Mental-State Reasoning for Precision Intervention
• Incumbent Advantage: Brand Bias and Cognitive Manipulation Dynamics in LLM Recommendation Systems