AIMC Topic: Reinforcement Schedule

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Extending unified-theory-of-reinforcement neural networks to steady-state operant behavior.

Behavioural processes Mar 24, 2016
The unified theory of reinforcement has been used to develop models of behavior over the last 20 years (Donahoe et al., 1993). Previous research has focused on the theory's concordance with the respondent behavior of humans and animals. In this exper...
Neural Networks, Computer Reinforcement, Psychology Choice Behavior Psychological Theory Conditioning, Operant Reinforcement Schedule
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Unified-theory-of-reinforcement neural networks do not simulate the blocking effect.

Behavioural processes Aug 28, 2015
For the last 20 years the unified theory of reinforcement (Donahoe et al., 1993) has been used to develop computer simulations to evaluate its plausibility as an account for behavior. The unified theory of reinforcement states that operant and respon...
Neural Networks, Computer Computer Simulation Data Interpretation, Statistical Reinforcement, Psychology Conditioning, Classical Conditioning, Operant Reinforcement Schedule
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Machine learning to detect schedules using spatiotemporal data of behavior: A proof of concept.

Journal of the experimental analysis of behavior Jul 1, 2025
Traditionally, the experimental analysis of behavior has relied on the single discrete response paradigm (e.g., key pecks, lever presses, screen clicks) to identify behavioral patterns. However, the development and availability of new technology allo...
Neural Networks, Computer Machine Learning Algorithms Animals Male Spatio-Temporal Analysis Rats Support Vector Machine Proof of Concept Study Rats, Long-Evans Conditioning, Operant Reinforcement Schedule
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