Partially Observable Markov Decision Processes (POMDPs) and Robotics
, 2021 Planning under uncertainty is critical to robotics. The Partially Observable Markov Decision Process (POMDP) is a mathematical framework for such planning problems. It is powerful due to its careful quantification of the non-deterministic effects of actions and partial observability of the states.
Hanna Kurniawati
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Human-in-the-Loop Synthesis for Partially Observable Markov Decision Processes [PDF]
2018 Annual American Control Conference (ACC), 2018 We study planning problems where autonomous agents operate inside environments that are subject to uncertainties and not fully observable. Partially observable Markov decision processes (POMDPs) are a natural formal model to capture such problems. Because of the potentially huge or even infinite belief space in POMDPs, synthesis with safety guarantees ...
Steven Carr +4 more
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An algorithm to create model file for Partially Observable Markov Decision Process for mobile robot path planning [PDF]
MethodsXThe Partially Observable Markov Decision Process (POMDP), a mathematical framework for decision-making in uncertain environments suffers from the curse of dimensionality.
Shripad V. Deshpande +3 more
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A Method for Speeding Up Value Iteration in Partially Observable Markov Decision Processes [PDF]
arXiv, 2013 We present a technique for speeding up the convergence of value iteration for partially observable Markov decisions processes (POMDPs). The underlying idea is similar to that behind modified policy iteration for fully observable Markov decision processes (MDPs). The technique can be easily incorporated into any existing POMDP value iteration algorithms.
Nevin L. Zhang +2 more
arxiv +3 more sources
A primer on partially observable Markov decision processes (POMDPs) [PDF]
Methods in Ecology and Evolution, 2021 AbstractPartially observable Markov decision processes (POMDPs) are a convenient mathematical model to solve sequential decision‐making problems under imperfect observations. Most notably for ecologists, POMDPs have helped solve the trade‐offs between investing in management or surveillance and, more recently, to optimise adaptive management problems ...
Iadine Chadès +4 more
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Structural Results for Partially Observed Markov Decision Processes [PDF]
arXiv, 2015 This article provides an introductory tutorial on structural results in partially observed Markov decision processes (POMDPs). Typically, computing the optimal policy of a POMDP is computationally intractable. We use lattice program- ming methods to characterize the structure of the optimal policy of a POMDP without brute force computations.
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When to monitor or control: Informed invasive species management using a partially observable Markov decision process (POMDP) framework [PDF]
Methods in Ecology and EvolutionResource allocation for invasive species management requires information about the size of the invasive population, which may be expensive and time‐consuming to obtain.
Thomas K. Waring +3 more
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MathematicsThis research investigates the joint optimization of maintenance and spare unit management for series systems composed of multiple heterogeneous units.
Nozomu Ogura, Mizuki Kasuya, Lu Jin
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Automated handwashing assistance for persons with dementia using video and a partially observable Markov decision process [PDF]
Computer Vision and Image Understanding, 2010 Jesse Hoey +5 more
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Wireless Downlink Scheduling with Deadline Constraint for Realistic Channel Observation Environment [PDF]
Jisuanji kexue, 2021 Deadline-constrained wireless downlink transmissions,which have been widely used for a variety of real-time communication services that are related to the national economy and the people's livelihood,require each packet to be delivered in an ultra ...
ZHANG Fan, GONG Ao-yu, DENG Lei, LIU Fang, LIN Yan, ZHANG Yi-jin
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