AoI-MDP: An AoI Optimized Markov Decision Process (Student Abstract)
Systems and Control
2026-05-19 v1 Systems and Control
Abstract
Ocean exploration places high demands on autonomous underwater vehicles, especially when there's observation delay. We propose age of information optimized Markov decision process (AoI-MDP) to enhance underwater tasks by modeling observation delay as signal delay and including it in the state space. AoI-MDP also introduces wait time in the action space and integrates AoI with reward functions, optimizing information freshness and decision-making using reinforcement learning. Simulations show AoI-MDP outperforms the standard MDP, demonstrating superior performance, feasibility, and generalization in underwater tasks. To accelerate relevant research, we have made the codes available as open-source at https://github.com/Xiboxtg/AoI-MDP.
Keywords
Cite
@article{arxiv.2605.16777,
title = {AoI-MDP: An AoI Optimized Markov Decision Process (Student Abstract)},
author = {Yimian Ding and Jingzehua Xu and Yiyuan Yang and Guanwen Xie and Xinqi Wang and Shuai Zhang},
journal= {arXiv preprint arXiv:2605.16777},
year = {2026}
}