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Hearts Gym: Learning Reinforcement Learning as a Team Event

arXiv 2209.05466 ↗First posted 7 Sep 2022cs.CY cs.AI cs.LGcited by 0

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Abstract (arXiv)

Amidst the COVID-19 pandemic, the authors of this paper organized a Reinforcement Learning (RL) course for a graduate school in the field of data science. We describe the strategy and materials for creating an exciting learning experience despite the ubiquitous Zoom fatigue and evaluate the course qualitatively. The key organizational features are a focus on a competitive hands-on setting in teams, supported by a minimum of lectures providing the essential background on RL. The practical part of the course revolved around Hearts Gym, an RL environment for the card game Hearts that we developed as an entry-level tutorial to RL. Participants were tasked with training agents to explore reward shaping and other RL hyperparameters. For a final evaluation, the agents of the participants competed against each other.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 6 of its 19 references that are in the map. First posted on arXiv 7 Sep 2022.

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6 of 19 references.

References · 6

  1. 2017AirSim: High-Fidelity Visual and Physical Simulation for Autonomous Vehiclescited by 523
  2. 2017StarCraft II: A New Challenge for Reinforcement Learningcited by 274
  3. 2020PettingZoo: Gym for Multi-Agent Reinforcement Learningcited by 220
  4. 2019OpenSpiel: A Framework for Reinforcement Learning in Gamescited by 186
  5. 2019RLCard: A Toolkit for Reinforcement Learning in Card Gamescited by 35
  6. 2019DeepRacer: Educational Autonomous Racing Platform for Experimentation with Sim2Real Reinforcement Learningcited by 13

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