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Related Experiment Videos

Choice and multiple reinforcers.

J Moore

    Journal of the Experimental Analysis of Behavior
    |January 1, 1982
    PubMed
    Summary
    This summary is machine-generated.

    Pigeons preferred schedules where reinforcement density signaled options. However, they showed no preference when only the number of reinforcers varied, indicating local variables influence choice more than molar ones.

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    Area of Science:

    • Behavioral psychology
    • Animal cognition
    • Operant conditioning

    Background:

    • Understanding choice behavior in animals is crucial for behavioral science.
    • Reinforcement schedules significantly impact decision-making processes.
    • Distinguishing between local and molar variables in reinforcement is key to predicting choice.

    Purpose of the Study:

    • To investigate pigeon preference between mixed and multiple terminal-link schedules.
    • To determine if reinforcement density or number of reinforcers per cycle drives preference.
    • To assess the influence of local versus molar variables on choice behavior.

    Main Methods:

    • Utilized the concurrent-chains procedure with pigeons.
    • Presented two-component mixed and multiple schedules of reinforcement.

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  • Varied component differentiation based on reinforcement density and number of reinforcers per cycle.

    • Main Results:

    • Pigeons preferred the multiple schedule when components differed in reinforcement density.
    • Pigeons were indifferent when components differed solely in the number of reinforcers per cycle.
    • Preference was evoked by local variables (interval to first reinforcer) but not molar variables (total reinforcers).

    Conclusions:

    • Reinforcement density, a local variable, is sufficient to differentiate schedule components and evoke preference.
    • The number of reinforcers, a molar variable, was insufficient to differentiate components or influence choice.
    • Findings highlight the importance of local variables in predicting choice behavior under complex reinforcement schedules.