mlsanityData to 7 Oct 2026

PantheonRL: A MARL Library for Dynamic Training Interactions

arXiv 2112.07013 ↗First posted 13 Dec 2021cs.MA cs.AI cs.LGcited by 10

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Abstract (arXiv)

We present PantheonRL, a multiagent reinforcement learning software package for dynamic training interactions such as round-robin, adaptive, and ad-hoc training. Our package is designed around flexible agent objects that can be easily configured to support different training interactions, and handles fully general multiagent environments with mixed rewards and n agents. Built on top of StableBaselines3, our package works directly with existing powerful deep RL algorithms. Finally, PantheonRL comes with an intuitive yet functional web user interface for configuring experiments and launching multiple asynchronous jobs. Our package can be found at https://github.com/Stanford-ILIAD/PantheonRL.

Key facts. Cited by 10 papers in the map (data through 7 Oct 2026). Builds on 5 of its 7 references that are in the map. First posted on arXiv 13 Dec 2021.

Builds on

5 of 7 references.

References · 5

  1. 2016OpenAI Gymcited by 1,684
  2. 2019The StarCraft Multi-Agent Challengecited by 589
  3. 2020PettingZoo: Gym for Multi-Agent Reinforcement Learningcited by 209
  4. 2013Hidden Parameter Markov Decision Processes: A Semiparametric Regression Approach for Discovering Latent Task Parametrizationscited by 68
  5. 2021Mava: a research library for distributed multi-agent reinforcement learning in JAXcited by 14

Built on by

Cited by year

Citing papers per year: 2023: 6; 2024: 2; 2025: 2.

10 papers.

  1. 2023PECAN: Leveraging Policy Ensemble for Context-Aware Zero-Shot Human-AI Coordinationcited by 25
  2. 2023Diverse Conventions for Human-AI Collaborationcited by 14
  3. 2024FightLadder: A Benchmark for Competitive Multi-Agent Reinforcement Learningcited by 13
  4. 2023Tackling Cooperative Incompatibility for Zero-Shot Human-AI Coordinationcited by 12
  5. 2023Mixture of personality improved Spiking actor network for efficient multi-agent cooperationcited by 4
  6. 2025Deep Reinforcement Learning for Job Scheduling and Resource Management in Cloud Computing: An Algorithm-Level Reviewcited by 4
  7. 2024BCR-DRL: Behavior- and Context-aware Reward for Deep Reinforcement Learning in Human-AI Coordinationcited by 3
  8. 2025Who is Helping Whom? Analyzing Inter-dependencies to Evaluate Cooperation in Human-AI Teamingcited by 2
  9. 2023marl-jax: Multi-Agent Reinforcement Leaning Frameworkcited by 1
  10. 2023Learning Top-k Subtask Planning Tree based on Discriminative Representation Pre-training for Decision Makingcited by 0