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Temporal Difference Learning Waveform Selection

JOURNAL OF COMPUTERS 2010年第9期5卷 1394-1401页

作者： Wang, Bin Wang, Jinkuan Song, Xin Han, Yinghua Nrotheastern Univ Shenyang Liaoning Peoples R China Nrotheastern Univ Qinhuangdao Qinhuangdao Peoples R China

How to optimally decide or select the radar waveform for next transmission based on the observation of past radar returns is one of the important problems in cognitive radar. In this paper, stochastic dynamic programming model is proposed. Then temporal difference learning method is used to realize the adaptivity of waveform selection. The simulation results show that the uncertainty of state estimation using temporal difference learning is less than that using fixed waveform. Temporal difference learning method approaches the optimal waveform selection scheme but has lower computational cost. Finally, the whole paper is summarized.

关键词： waveform selection stochastic dynamic programming temporal difference learning cognitive radar

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COW CULLING DECISIONS ADAPTED FOR MANAGEMENT WITH CART

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AMERICAN JOURNAL OF AGRICULTURAL ECONOMICS 1994年第2期76卷 237-249页

作者： TRONSTAD, R GUM, R UNIV ARIZONA DEPT AGR & RESOURCE ECON TUCSON AZ 85721 USA

A stochastic dynamic programming (DP) model of range cow culling decisions incorporating market price uncertainties and dynamics of biological productivity was solved for biannual and annual calving systems. Decision trees were generated from the DP solutions using the Classification and Regression Trees (CART) methodology. The decision trees captured over 99% of the optimal DP returns from both biannual and spring-only calving. CART culling criteria in conjunction with dual-season calving increased wealth by 7% compared to optimal DP culling decisions with spring-only calving, and by 10% compared to a more traditional strategy of culling all open cows.

关键词： CART CULLING RANGE COWS DECISION TREES FERTILITY MARKET CONDITIONS stochastic dynamic programming

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stochastic rangeland use under capital constraints

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AMERICAN JOURNAL OF AGRICULTURAL ECONOMICS 2007年第3期89卷 805-817页

作者： Kobayashi, Mimako Howitt, Richard E. Jarvis, Lovell S. Laca, Emilio A. Univ Calif Davis CADMS Sch Vet Med Davis CA 95616 USA Univ Calif Davis Dept Agr & Resource Econ Davis CA 95616 USA Univ Calif Davis Dept Plant Sci Davis CA 95616 USA

The stocking density on Kazakhstan's extensive rangelands is well below traditional levels. To analyze dynamic flock performance, we develop a stochastic dynamic programming model for livestock systems with stochastic forage production. The model contains continuous five state and 12 control variables, allowing improved characterization of the biophysical relationships and economic tradeoffs inherent in such systems. Most Kazakhstan herders have restricted access to capital. The model indicates that the cost of capital strongly affects flock size and productivity. We conclude that capital constraints are important to explaining the current low stocking density. Improving capital markets in rural areas warrants policy attention.

关键词： extensive livestock production Kazakhstan stochastic dynamic programming transition economies

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Optimal fire management for maintaining community diversity

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ECOLOGICAL APPLICATIONS 1999年第3期9卷 880-892页

作者： Richards, SA Possingham, HP Tizard, J Univ Adelaide Dept Appl & Mol Ecol Glen Osmond SA 5064 Australia

Disturbance events strongly influence the dynamics of plant and animal populations within nature reserves. Although many models predict the patterns of succession following a disturbance event, it is often unclear how these models can be used to help make management decisions about disturbances. In this paper we consider the problem of managing fire in Ngarkat Conservation Park (CP), South Australia, Australia. We present a mathematical model of community succession following a fire disturbance event. Ngarkat CP is, a key habitat for several nationally rare and threatened species of birds, and because these species prefer different successional communities, we assume that the primary management objective is to maintain community diversity within the park. More specifically, the aim of management is to keep at least a certain fraction of the park, (e.g., 20%), in each of three successional stages. We assume that each year a manager may do one of the following: let wildfires burn unhindered, fight wildfires, or perform controlled burns. We apply stochastic dynamic programming to identify which of these three strategies is optimal, i.e., the one most likely to promote community diversity. Model results indicate that the optimal management strategy depends on the current state of the park, the cost associated with each strategy, and the time frame over which the manager has set his/her goal.

关键词： Australia biodiversity conservation community succession decision theory disturbance events, stochastic fire management model managing wildfire to promote biodiversity Markov model modeling disturbance events stochastic dynamic programming succession

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Optimal sequential grain marketing decisions under risk aversion and price uncertainty

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AMERICAN JOURNAL OF AGRICULTURAL ECONOMICS 1997年第4期79卷 1140-1152页

作者： Blakeslee, L Washington State Univ Pullman WA 99164 USA

A method is developed to find sequences of expected utility maximizing decisions under risk aversion when random elements are time-dependent and additive separable utility of income is implausible. A Taylor-series approximation to expected utility is used. In an application to marketing stored wheat, expected seasonal sales patterns, early fractional sales of total inventory for risk reduction, and negative skewness in resulting income distributions are noted. Sensitivity to the number of income distribution moments used to approximate expected utility is examined. Six moments produce a good approximation. Use of only mean and variance can give doubtful results.

关键词： price risk risk management stochastic dynamic programming wheat marketing

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IMPACTS OF WATER SUPPLY UNCERTAINTY AND STORAGE ON EFFICIENT IRRIGATION TECHNOLOGY ADOPTION

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NATURAL RESOURCE MODELING 2014年第1期27卷 1-24页

作者： Bhaduri, Anik Manna, Utpal Univ Bonn Global Water Syst Project GWSP D-53113 Bonn Germany Indian Inst Sci Educ & Res IISER Sch Math Thiruvananthapuram 695016 Kerala India

In the framework of a stochastic dynamic programming model, the paper investigates the impact of water supply uncertainty and storage at farm level on adoption of efficient irrigation technologies under a flexible water price regime. We find that even a flexible water pricing cannot guarantee higher adoption of efficient irrigation technology in all cases. Results of the paper indicate that if a farmer invests in water storage capacity, then the value of efficient usage of water increases, and the rate of adoption of efficient irrigation technology will be higher. It establishes a complementarity relationship between investments in storage capacity and adoption of efficient irrigation technology. The relationship becomes stronger with increasing variance in water supply. In a situation without any option to store water at the farm level, we find a negative relationship between investment in efficient irrigation technology and water variability. However, numerical analysis results suggest that a risk averse farmer may invest more in efficient irrigation only if the variance in water supply is very high.

关键词： stochastic dynamic programming water pricing adoption of efficient irrigation technology

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Assessing the value of monitoring to biological inference and expected management performance for a European goose population

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JOURNAL OF APPLIED ECOLOGY 2023年第1期60卷 132-145页

作者： Johnson, Fred A. Madsen, Jesper Clausen, Kevin K. Frederiksen, Morten Jensen, Gitte H. Aarhus Univ Dept Ecosci Aarhus C Denmark Aarhus Univ Dept Ecosci Roskilde Denmark

Informed conservation and management of wildlife require sufficient monitoring to understand population dynamics and to direct conservation actions. Because resources available for monitoring are limited, conservation practitioners must strive to make monitoring as cost-effective as possible. Our focus was on assessing the value of monitoring to the adaptive harvest management (AHM) programme for pink-footed geese Anser brachyrhynchus. We conducted a retrospective analysis to assess the costs and benefits of a capture-mark-resight (CMR) programme, a productivity survey and biannual population censuses. Using all available data, we fit an integrated population model (IPM) and assumed that inference derived from it represented the benchmark against which reduced monitoring was to be judged. We then fit IPMs to reduced sets of monitoring data and compared their estimates of demographic parameters and expected management performance against the benchmark IPM. Costs and the precision and accuracy of key demographic parameters decreased with the elimination of monitoring data. Eliminating the CMR programme, while maintaining other monitoring instruments, resulted in the greatest cost savings, usually with small effects on inferential reliability. Productivity surveys were also expensive and some reduction in survey effort may be warranted. The biannual censuses were inexpensive and generally increased inferential reliability. The expected performance of AHM strategies was surprisingly robust to a loss of monitoring data. We attribute this result to explicit consideration of parametric uncertainty in harvest-strategy optimization and the fact that a broad range of population sizes is acceptable to stakeholders. Synthesis and applications. Our study suggests that existing or potential monitoring instruments for wildlife populations should be scrutinized as to their cost-effectiveness for improving biological inference and management performance. Using Svalbard pink-footed g

关键词： adaptive management harvest integrated population model monitoring optimization pink-footed geese stochastic dynamic programming value of information

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Optimal responses to environmental and physiological constraints: Evaluation of a model for a planktivore

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SARSIA 1997年第2期82卷 113-128页

作者： Rosland, R Department of Fisheries and Marine Biology University of Bergen Bergen High Technology Center Bergen N-5020 Norway

A numeric model for the life history of the mesopelagic planktivore Maurolicus muelleri is tested for sensitivity to different parameter values. The model is based on stochastic dynamic programming with decision variables for habitat choice (depth) and energy allocation (between somatic or reproductive growth). The model includes sub-models to represent the foraging, mortality and growth processes. The parameters that induce large changes in most variables are those related to foraging and visual predation risk. By inducing changes in the strategic habitat choices, they have a large impact on other processes like growth, survival and reproduction. The other parameters tested generally have local impact (e.g, on weight or survival), with less impact on other variables of the model. Seasonality in prey abundance and larval survival both have to be present for the model to predict the seasonal strategies observed for M. muelleri in Norwegian fjords. Size dependent factors in the prey encounter, predation and growth processes may explain the observed differences amongst different sized groups of the fish. The strategies predicted for different seasons and size groups of fish, however, are very dependent on the ratio between food abundance and visual predation risk. Size dependent processes in general seem important to understand the selective forces that shape the observed life history patterns of the fish.

关键词： life history mesopelagic fish habitat choice stochastic dynamic programming

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Risk inflation of sequential tests controlled by alpha investing

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JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION 2015年第18期85卷 3613-3627页

作者： Foster, Dean P. Stine, Robert A. Univ Penn Wharton Sch Dept Stat Philadelphia PA 19104 USA

Streaming feature selection is a greedy approach to variable selection that evaluates potential explanatory variables sequentially. It selects significant features as soon as they are discovered rather than testing them all and picking the best one. Because it is so greedy, streaming selection can rapidly explore large collections of features. If significance is defined by an alpha investing protocol, then the rate of false discoveries will be controlled. The focus of attention in variable selection, however, should be on fit rather than hypothesis testing. Little is known, however, about the risk of estimators produced by streaming selection and how the configuration of these estimators influences the risk. To meet these needs, we provide a computational framework based on stochastic dynamic programming that allows fast calculation of the minimax risk of a sequential estimator relative to an alternative. The alternative can be data driven or derived from an oracle. This framework allows us to compute and contrast the risk inflation of sequential estimators derived from various alpha investing rules. We find that a universal investing rule performs well over a variety of models and that estimators allowed to have larger than conventional rates of false discoveries produce generally smaller risk.

关键词： stochastic dynamic programming testimator variable selection

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Decision support program for long term production planning of hydro-power plants with major reservoirs

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UPB Scientific Bulletin, Series D: Mechanical Engineering 2008年第4期70卷 137-146页

作者： Popa, Radu Dragomirescu, Andrei Popa, Bogdan Faculty of Power Engineering University Politehnica Bucharest Romania

The paper presents a decision support program who takes into consideration the system which consists in the ten important reservoirs with the associated hydropower plants. This program enables the selection of the strategic operation policy for the next month, or for a certain number of oncoming months, depending on reservoirs levels at the beginning of the month, and on the average monthly anticipated affluent flows;it suggests the most suitable operation solution according to an optimization model of stochastic dynamic programming.

关键词： Decision support program Optimal hydropower reservoir operation stochastic dynamic programming

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