mlsanityData to 14 Oct 2026

Agent-Arena: A General Framework for Evaluating Control Algorithms

arXiv 2504.06468 ↗First posted 8 Apr 2025cs.RO cs.AI cs.SEcited by 1

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Abstract (arXiv)

Robotic research is inherently challenging, requiring expertise in diverse environments and control algorithms. Adapting algorithms to new environments often poses significant difficulties, compounded by the need for extensive hyper-parameter tuning in data-driven methods. To address these challenges, we present Agent-Arena, a Python framework designed to streamline the integration, replication, development, and testing of decision-making policies across a wide range of benchmark environments. Unlike existing frameworks, Agent-Arena is uniquely generalised to support all types of control algorithms and is adaptable to both simulation and real-robot scenarios. Please see our GitHub repository https://github.com/halid1020/agent-arena-v0.

Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 22 of its 33 references that are in the map. First posted on arXiv 8 Apr 2025.

Builds on

22 of 33 references.

References · 22

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10 more
  1. 2020dm_control: Software and Tasks for Continuous Controlcited by 375
  2. 2020Transporter Networks: Rearranging the Visual World for Robotic Manipulationcited by 344
  3. 2023Minigrid & Miniworld: Modular & Customizable Reinforcement Learning Environments for Goal-Oriented Taskscited by 327
  4. 2020RoboTHOR: An Open Simulation-to-Real Embodied AI Platformcited by 193
  5. 2016ViZDoom: A Doom-based AI Research Platform for Visual Reinforcement Learningcited by 179
  6. 2018Dopamine: A Research Framework for Deep Reinforcement Learningcited by 122
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  10. 2019Arena: A General Evaluation Platform and Building Toolkit for Multi-Agent Intelligencecited by 9

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