Monitoring as a partially observable decision problem |
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Affiliation: | 1. Department of Agricultural and Resource Economics, North Carolina State University, Box 8109, Raleigh, NC 27695, USA;2. U.S. Forest Service Northern Research Station, 1992 Folwell Avenue, St. Paul, MN 55108, USA;1. Statistics Norway, Research Department, Norway;2. Norwegian University of Life Sciences, School of Economics and Business and Statistics Norway, Research Department, Norway;3. University of Stavanger, Department of Industrial Economics and Risk Management, Norway;1. School of Resource and Environmental Science, Hubei University, Wuhan, Hubei 430062, PR China;2. Institute of Plant Protection, Henan Academy of Agricultural Sciences, Zhengzhou 450002, PR China;3. Institute of Plant Protection & Soil Science, Hubei Academy of Agricultural Sciences, Wuhan 430070, PR China;1. Universidad Nacional de Colombia Sede Bogotá, Physics Department, Colombia;2. Universidad Nacional de Colombia Sede Medellin, School of Physics, A.A: 3840, Medellin 050034, Colombia;1. Department of Chemical Engineering and Materials Science, Stevens Institute of Technology, Hoboken, NJ 07030, USA;2. Institute of Photonics and Electronics AS CR, v.v.i., Chaberska 57, Prague 8 18251, Czech Republic |
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Abstract: | Monitoring is an important and costly activity in resource management problems such as containing invasive species, protecting endangered species, preventing soil erosion, and regulating contracts for environmental services. Recent studies have viewed optimal monitoring as a Partially Observable Markov Decision Process (POMDP), which provides a framework for sequential decision making under stochastic resource dynamics and uncertainty about the resource state. We present an overview of the POMDP framework and its applications to resource monitoring. We discuss the concept of the information content provided by monitoring systems and illustrate how information content affects optimal monitoring strategies. Finally, we demonstrate how the timing of monitoring in relation to resource treatment and transition can have substantial effects on optimal monitoring strategies. |
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Keywords: | Environmental monitoring Dynamic programming Partial observability Value of information POMDP |
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