Lifting DecPOMDPs for Nanoscale Systems -- A Work in Progress
Artificial Intelligence
2021-10-19 v1
Abstract
DNA-based nanonetworks have a wide range of promising use cases, especially in the field of medicine. With a large set of agents, a partially observable stochastic environment, and noisy observations, such nanoscale systems can be modelled as a decentralised, partially observable, Markov decision process (DecPOMDP). As the agent set is a dominating factor, this paper presents (i) lifted DecPOMDPs, partitioning the agent set into sets of indistinguishable agents, reducing the worst-case space required, and (ii) a nanoscale medical system as an application. Future work turns to solving and implementing lifted DecPOMDPs.
Cite
@article{arxiv.2110.09152,
title = {Lifting DecPOMDPs for Nanoscale Systems -- A Work in Progress},
author = {Tanya Braun and Stefan Fischer and Florian Lau and Ralf Möller},
journal= {arXiv preprint arXiv:2110.09152},
year = {2021}
}
Comments
Accepted at the Tenth International Workshop on Statistical Relational AI (StarAI-2021)