Guidance for Using State-and Prediction-Based Theory
Guidance for Using State-and Prediction-Based Theory
This chapter outlines the guidance on using state- and prediction-based theory (SPT) to build models of populations and communities of adaptive individuals, detailing five steps unique to SPT. The most important aspect of SPT to remember is that one is not trying to build optimal, or even necessarily accurate, models of how an organism's behavior affects its future fitness. Instead, one is trying to find simplistic models that produce realistic behavior in contexts where optimization is impossible. While SPT can be used like dynamic state variable modeling (DSVM), as a framework for thinking about and modeling how an individual makes a particular decision, its main purpose is to model adaptive trade-off decisions in individual-based population models. Thus, using SPT is part of the larger process of developing, analyzing, and applying an IBM to address population-level questions, and the five steps therefore include that process.
Keywords: state-based theory, prediction-based theory, populations, communities, adaptive individuals, dynamic state variable modeling, adaptive trade-off decisions, individual-based population models
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