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Lifting DecPOMDPs for Nanoscale Systems -- A Work in Progress

arXiv 2110.09152 ↗First posted 18 Oct 2021cs.AIcited by 0

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Abstract (arXiv)

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.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 3 of its 29 references that are in the map. First posted on arXiv 18 Oct 2021.

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3 of 29 references.

References · 3

  1. 2014Tractability through Exchangeability: A New Perspective on Efficient Probabilistic Inferencecited by 23
  2. 2019Generating and Sampling Orbits for Lifted Probabilistic Inferencecited by 3
  3. 2020Exploring Unknown Universes in Probabilistic Relational Modelscited by 1

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