Quantitative analysis of behavior is the application of mathematical models--conceptualized from the robust corpus of environment-behavior-consequence interactions in published behavioral science--to the experimental analysis of behavior. The aim is to describe and/or predict relations between varying levels of independent environmental variables and dependent behavioral variables. The parameters in the models hopefully have theoretical meaning beyond their use in fitting models to data. The field was founded by Richard Herrnstein (1961) when he introduced the matching law to quantify the behavior of organisms working on concurrent schedules of reinforcement.
The field has integrated models from economics, zoology, philosophy, political science (including voter behavior) and psychology, especially mathematical psychology of which it is a branch. The field is represented by the Society for Quantitative Analysis of Behavior. Quantitative analysis of behavior addresses the following topics among others: behavioral economics, behavioral momentum, connectionist systems or neural networks, integration, hyperbolic discounting including the delay reduction hypothesis, foraging, hunting, errorless learning, creativity, learning, and the Rescorla-Wagner model, matching law, melioration, scalar expectancy, signal detection, neural hysteresis, and reinforcement control.