2025/04/08 by Kadi, Halid Abdulrahim, Terzić, Kasim · 1 citation
#Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Robotics (cs.RO) #Software Engineering (cs.SE)
paper · doi:10.48550/arxiv.2504.06468
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.