Inverse Reinforcement Learning in Swarm Systems

  title={Inverse Reinforcement Learning in Swarm Systems},
  author={Adrian Sosic and Wasiur R. KhudaBukhsh and Abdelhak M. Zoubir and Heinz Koeppl},
Inverse reinforcement learning (IRL) has become a useful tool for learning behavioral models from demonstration data. However, IRL remains mostly unexplored for multi-agent systems. In this paper, we show how the principle of IRL can be extended to homogeneous large-scale problems, inspired by the collective swarming behavior of natural systems. In particular, we make the following contributions to the field: 1) We introduce the swarMDP framework, a subclass of decentralized partially… CONTINUE READING