Results 251 to 260 of about 937,585 (275)

A Partially Observed Markov Decision Process for Dynamic Pricing

Management Science, 2005
In this paper, we develop a stylized partially observed Markov decision process (POMDP) framework to study a dynamic pricing problem faced by sellers of fashion-like goods. We consider a retailer that plans to sell a given stock of items during a finite sales season.
Yossi Aviv, Amit Pazgal
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Approximate planning with hierarchical partially observable Markov decision process models for robot navigation

Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292), 2002
We propose and investigate a planning framework based on the hierarchical partially observable Markov decision process model (HPOMDP), and apply it to robot navigation.
Georgios Theocharous, S. Mahadevan
semanticscholar   +1 more source

Adaptive Multiview Target Classification in Synthetic Aperture Sonar Images Using a Partially Observable Markov Decision Process

IEEE Journal of Oceanic Engineering, 2012
The problem of classifying targets in sonar images from multiple views is modeled as a partially observable Markov decision process (POMDP). This model allows one to adaptively determine which additional views of an object would be most beneficial in ...
V. Myers, David P. Williams
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A partially observable discrete time Markov decision process with a fractional discounted reward

, 2017
We give a new partially observable discrete time Markov decision model with general state and action spaces, under a fractional discounted criterion. In order to discuss an optimal policy for this model, by using the parametric method we transform this ...
Teruo Tanaka
semanticscholar   +1 more source

Partially observable Markov decision processes with reward information [PDF]

2004 43rd IEEE Conference on Decision and Control (CDC) (IEEE Cat. No.04CH37601), 2004
In a partially observable Markov decision process (POMDP), if the reward can be observed at each step, then the observed reward history contains information for the unknown state. This information, in addition to the information contained in the observation history, can be used to update the state probability distribution.
Xianping Guo, Xi-Ren Cao
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Endangered Seabird Habitat Management as a Partially Observable Markov Decision Process

Marine Resource Economics, 2010
The marbled murrelet (Brachyramphus marmoratus) is an endangered seabird that nests in coastal forests from Alaska to California. The value of these forests for human use, coupled with the difficulty of determining whether a forest stand is occupied by ...
David. Tomberlin
semanticscholar   +1 more source

Algorithms for partially observable Markov decision processes

1988
The thesis develops methods to solve discrete-time finite-state partially observable Markov decision processes. For the infinite horizon problem, only discounted reward case is considered. Several new algorithms for the finite horizon and the infinite horizon problems are developed. For the finite horizon problem, two new algorithms are developed. The
Hsien-Te Cheng, Shelby Brumelle
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A tutorial on partially observable Markov decision processes

Journal of Mathematical Psychology, 2009
Abstract The partially observable Markov decision process (POMDP) model of environments was first explored in the engineering and operations research communities 40 years ago. More recently, the model has been embraced by researchers in artificial intelligence and machine learning, leading to a flurry of solution algorithms that can identify optimal ...
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Probabilistic Majorization of Partially Observable Markov Decision Processes

2023
Markov Decision Processes (MDPs) are wielded by the Reinforcement Learning and control community as a framework to bestow artificial agents with the ability to make autonomous decisions. Control as Inference (CaI) is a tangent research direction that aims to recast optimal decision making as an instance of probabilistic inference, with the dual hope to
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Misplaced item search in a warehouse using an RFID-based Partially Observable Markov Decision Process (POMDP) model

IEEE International Conference on Automation Science and Engineering, 2009
Inventory misplacement and inaccuracies contribute significantly to the operational expense of the overall supply chain. Radio Frequency Identification (RFID) technology has gained prominence as a solution to this approach.
S. Hariharan, S. Bukkapatnam
semanticscholar   +1 more source