Back to Research papers
Research paper index

AoI-MDP: An AoI Optimized Markov Decision Process (Student Abstract)

Yimian Ding, Jingzehua Xu, Yiyuan Yang, Guanwen Xie, Xinqi Wang, Shuai Zhang

arXiv:2605.16777Published May 16, 20260 citations
  • eess.SY
  • action
  • reinforcement learning

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.

Read the original paper

This page indexes public paper metadata. The manuscript remains with its original publisher and authors.