Reinforcement contingencies and social reinforcement are ubiquitous phenomena in applied behavior analysis. This discussion paper is divided into two sections. In the first section, reinforcement contingencies are discussed in terms of the necessary and sufficient conditions for reinforcement effects. Response-stimulus dependencies, conditional probabilities, and contiguity are discussed as pos...

This study uses a curve-fitting approach to evaluate the effects of drugs on reinforced responding in rats. The subjects obtained reinforcement according to a series of five different variable-interval schedules (a five-component multiple schedule). For each rat, pimozide, a neuroleptic, decreased response rate, and the decrease was associated with (1) a decrease in the estimated asymptotic res...

Basic researchers, but not most applied researchers, have assumed that the behavior-decelerating effects of noncontingent reinforcement result at least partly from adventitious reinforcement of competing behaviors. The literature contains only sketchy evidence of these effects because few noncontingent reinforcement studies measure alternative behaviors. A laboratory model is presented in which...

Reinforcement learning is an attractive method of machine learning. However, as the state space of a given problem increases, reinforcement learning becomes increasingly inefficient. Hierarchical reinforcement learning is one method of increasing the efficiency of reinforcement learning. It involves breaking the overall goal of a problem into a hierarchy subgoals, and then attempting to achieve...

Reinforcement schemes represent the basis of the learning process for stochastic learning automata, generating their learning behavior. An automaton using a reinforcement scheme can decide the best action, based on past actions and environment responses. The aim of this paper is to introduce a new reinforcement scheme for stochastic learning automata. We test our schema and compare with other n...

Reinforcement and error-based processes are essential for motor learning, with the cerebellum thought to be required only for the error-based mechanism. Here we examined learning and retention of a reaching skill under both processes. Control subjects learned similarly from reinforcement and error-based feedback, but showed much better retention under reinforcement. To apply reinforcement to ce...

Learning complex skills is driven by reinforcement, which facilitates both online within-session gains and retention of the acquired skills. Yet, in ecologically relevant situations, skills are often acquired when mapping between actions and rewarding outcomes is unknown to the learning agent, resulting in reinforcement schedules of a stochastic nature. Here we trained subjects on a visuomotor ...

Although the effects of negative reinforcement on human behavior have been studied for a number of years, a comprehensive body of applied research does not exist at this time. This article describes three aspects of negative reinforcement as it relates to applied behavior analysis: behavior acquired or maintained through negative reinforcement, the treatment of negatively reinforced behavior, a...

The authors measured food reinforcement, polymorphisms of the dopamine D2 receptor (DRD2) and dopamine transporter (DAT1) genes, and laboratory energy intake in 29 obese and 45 nonobese humans 18-40 years old. Food reinforcement was greater in obese than in nonobese individuals, especially in obese individuals with the TaqI A1 allele. Energy intake was greater for individuals high in food reinf...