Dynamic Modeling in Behavioral Ecology
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A01=Colin Whitcomb Clark
A01=Marc Mangel
Alternative hypothesis
Author_Colin Whitcomb Clark
Author_Marc Mangel
Bayesian inference
Bayesian statistics
Behavioral ecology
Behavioral modeling
Biology
Biomass (ecology)
Calculation
Category=PSV
Category=PSVP
Central place foraging
Control function (econometrics)
Control theory
Decision theory
Decision-making
Density dependence
Dynamic programming
Ecology
Environmental factor
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Evolutionary biology
Evolutionary ecology
Expected value
Fecundity
Field experiment
Fitness function
Flocking (behavior)
Foraging
Group selection
Insect
Iteration
Loss function
Mathematical and theoretical biology
Mathematical optimization
Monte Carlo method
Natural selection
Optimal control
Optimal foraging theory
Optimization problem
Organism
Oviparity
Parameter
Parasitism
Phenotypic plasticity
Poisson distribution
Poisson point process
Population dynamics
Posterior probability
Predation
Prediction
Prior probability
Probability
Probability distribution
Production function
Random variable
Reinforcement learning
Reproductive value (population genetics)
Result
Risk aversion
Schematic
Selection algorithm
Sensitivity analysis
State variable
Stochastic differential equation
Stochastic dynamic programming
Stochastic optimization
Subroutine
Survival function
Theory
Trade-off
Trophic level
Utility
Zooplankton
Product details
- ISBN 9780691085067
- Weight: 454g
- Dimensions: 152 x 229mm
- Publication Date: 21 Jan 1989
- Publisher: Princeton University Press
- Publication City/Country: US
- Product Form: Paperback
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This book describes a powerful and flexible technique for the modeling of behavior, based on evolutionary principles. The technique employs stochastic dynamic programming and permits the analysis of behavioral adaptations wherein organisms respond to changes in their environment and in their own current physiological state. Models can be constructed to reflect sequential decisions concerned simultaneously with foraging, reproduction, predator avoidance, and other activities. The authors show how to construct and use dynamic behavioral models. Part I covers the mathematical background and computer programming, and then uses a paradigm of foraging under risk of predation to exemplify the general modeling technique. Part II consists of five "applied" chapters illustrating the scope of the dynamic modeling approach. They treat hunting behavior in lions, reproduction in insects, migrations of aquatic organisms, clutch size and parental care in birds, and movement of spiders and raptors. Advanced topics, including the study of dynamic evolutionarily stable strategies, are discussed in Part III.
