Dynamic Modeling in Behavioral EcologyThis 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. |
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... called “adaptationist paradigm” have arisen. Because we believe that these criticisms are cogent, and also because we believe that the modeling methodology presented in this book goes some distance (but certainly not all the way) ...
... called events. The probability that a certain event A occurs will be denoted by Pr(A) (read as “the probability of A,” or “the probability that A occurs”). Thus we will encounter expressions like Pr(animal survives T periods) and Pr(X(T) ...
... called the sample space of the experiment. The elements of S may be thought of as basic events. For example, suppose that S consists of the set of all possible 13-card bridge hands; A is the event that “the hand contains the Ace of ...
... called a discrete random variable, whereas a random variable capable of assuming a continuum of values is called BASIC PROBABILITY □ 15 1.2 Discrete Random Variables and Distributions.
... called a continuous random variable. An example of a discrete random variable would be the number of offspring produced by some animal. The body weight of an animal would be an example of a continuous random variable. (However, in ...
Contents
3 | |
9 | |
II Applications | |
III Additional Topics | |
Perspectives on Dynamic Modeling | |
References | |
Author Index | |
Subject Index | |