Adapting Exploratory Behaviour in Active Inference for Autonomous Driving

Sheida Nozari; Ali Krayani; Pablo Marin; Lucio Marcenaro; David Martín; Carlo S. Regazzoni

ICASSP 2023accepted0 citations

Adapting Exploratory Behaviour in Active Inference for Autonomous Driving

Sheida Nozari, Ali Krayani, Pablo Marin, Lucio Marcenaro, David Martín, Carlo S. Regazzoni

Abstract

Active inference is a probabilistic framework for modeling intelligent agent behaviours, which drives by the principle of minimizing free energy. In this paper, we integrate the imitation learning method with active inference to minimize the expected free energy under the supervision of an expert model. The proposed approach affords explainable decision-making as a combination of self-information and novelty-seeking or exploratory behavior in a hierarchical generative model. A lane-changing driving scenario is demonstrated to verify the efficiency of the proposed framework that outperforms conventional Reinforcement learning methods.

BibTeX

@inproceedings{icassp2023_adaptingexplorat,
  title = {Adapting Exploratory Behaviour in Active Inference for Autonomous Driving},
  author = {Sheida Nozari and Ali Krayani and Pablo Marin and Lucio Marcenaro and David Martín and Carlo S. Regazzoni},
  booktitle = {ICASSP 2023},
  year = {2023}
}