Imitation Learning based Alternative Multi-Agent Proximal Policy Optimization for Well-Formed Swarm-Oriented Pursuit Avoidance
On the map: Offline RL and imitation learning from data → Imitation learning methods
Abstract (arXiv)
Multi-Robot System (MRS) has garnered widespread research interest and fostered tremendous interesting applications, especially in cooperative control fields. Yet little light has been shed on the compound ability of formation, monitoring and defence in decentralized large-scale MRS for pursuit avoidance, which puts stringent requirements on the capability of coordination and adaptability. In this paper, we put forward a decentralized Imitation learning based Alternative Multi-Agent Proximal Policy Optimization (IA-MAPPO) algorithm to provide a flexible and communication-economic solution to execute the pursuit avoidance task in well-formed swarm. In particular, a policy-distillation based MAPPO executor is firstly devised to capably accomplish and swiftly switch between multiple formations in a centralized manner. Furthermore, we utilize imitation learning to decentralize the formation controller, so as to reduce the communication overheads and enhance the scalability. Afterwards, alternative training is leveraged to compensate the performance loss incurred by decentralization. The simulation results validate the effectiveness of IA-MAPPO and extensive ablation experiments further show the performance comparable to a centralized solution with significant decrease in communication overheads.
Key facts. No citing papers in the map yet (data through 14 Oct 2026). Placed in Imitation learning methods, one of 13 directions in Offline RL and imitation learning from data. Builds on 4 of its 9 references that are in the map. First posted on arXiv 6 Nov 2023.
Builds on
4 of 9 references.
References · 4
- 2017Multi-Agent Actor-Critic for Mixed Cooperative-Competitive Environmentscited by 1,558
- 2021The Surprising Effectiveness of PPO in Cooperative, Multi-Agent Gamescited by 942
- 2023Stochastic Graph Neural Network-based Value Decomposition for MARL in Internet of Vehiclescited by 7
- 2023Decentralized Adaptive Formation via Consensus-Oriented Multi-Agent Communicationcited by 1
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- 2022Decentralized Policy Optimization
- 2024A Local Information Aggregation based Multi-Agent Reinforcement Learning for Robot Swarm Dynamic Task Allocation
- 2025Multi-Agent Guided Policy Optimization
- 2024Multi-Robot Pursuit in Parameterized Formation via Imitation Learning
- 2019Decentralized Multi-Agents by Imitation of a Centralized Controller
- 2018PRIMAL: Pathfinding via Reinforcement and Imitation Multi-Agent Learning
- 2024Fully Decentralized Cooperative Multi-Agent Reinforcement Learning: A Survey
- 2025Generalizable Collaborative Search-and-Capture in Cluttered Environments via Path-Guided MAPPO and Directional Frontier Allocation