Preference, resistance to change, and the cumulative decision model

Area of Science:

• Behavioral Psychology
• Animal Behavior
• Reinforcement Learning

Background:

• Behavioral momentum theory posits that preference and resistance to change are linked to reinforcement history.
• Previous research by Nevin, Grace, and colleagues (1997-2002) explored these concepts using parametric manipulation of reinforcement variables.

Purpose of the Study:

• To review foundational and recent research on preference and resistance to change within the framework of behavioral momentum theory.
• To evaluate the efficacy of the cumulative decision model in accounting for preference and resistance to change data.

Main Methods:

• Review of parametric studies on preference and resistance to change.
• Analysis of data using the cumulative decision model.
• Examination of correlations between residuals from model fits.

Main Results:

• The cumulative decision model effectively explains both preference and resistance to change.
• The model accurately predicts increased sensitivity to reinforcer rate and magnitude with constant-duration components.
• Positive correlations between model residuals support behavioral momentum theory's predictions.

Conclusions:

• The cumulative decision model provides a robust framework for understanding preference and resistance to change.
• The model's proposed learning process, involving outcome comparison against a contextual average, may explain the acquisition of differential resistance to change.