SCHEDULES OF REINFORCEMENT WITH SKINNER

Actions that modify schedules of reinforcement

Many everyday activities involve the use of one action to modify the effects of another: When driving, shifting gears modifies the influence of pressing the gas pedal on acceleration; when cooking, the rate of adding a particular ingredient modifies the influence of stirring on viscosity. Here, we investigate a general ability to learn how to use actions to control schedules of reinforcement. I...

Assessing Animals’ Preferences: Concurrent Schedules of Reinforcement

Schedules of Reinforcement and Game Experience

The objective of this paper is to better understand the incentives and rewards structure in online serious games for crowds. We address the issue of feedback mechanisms with a focus on the relationship between game behavior and accumulated game scores (points). We posit that the score keeping system design is likely to inform us regarding patterns of participation in games. Our question is: wha...

Reinforcement Learning for Multi-purpose Schedules

In this paper, we present a learning technique for determining schedules for general devices that focus on a combination of two objectives. These objectives are user-convenience and gains in energy savings. The proposed learning algorithm is based on Fitted-Q Iteration (FQI) and analyzes the usage and the users of a particular device to decide upon the appropriate profile of start-up and shutdo...

On the applied use of progressive-ratio schedules of reinforcement.

Examination of responding under various schedule arrangements is a core component of many analyses of operant behavior. Much of the pioneering work in applied behavior analysis was bred from laboratory research involving the exposure of nonhuman subjects to a variety of schedule arrangements. For example, Reynolds (1961) described a multiple-schedule arrangement in which one component consisted...