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Reinforcement theory. Reinforcement theory is a limited effects media model applicable within the realm of communication. The theory generally states that people seek out and remember information that provides cognitive support for their pre-existing attitudes and beliefs. The main assumption that guides this theory is that people do not like ...
In behavioral psychology, reinforcement refers to consequences that increase the likelihood of an organism's future behavior, typically in the presence of a particular antecedent stimulus. [1] For example, a rat can be trained to push a lever to receive food whenever a light is turned on. In this example, the light is the antecedent stimulus ...
Institutions. University of Minnesota. Indiana University. Harvard University. Signature. Burrhus Frederic Skinner (March 20, 1904 – August 18, 1990) was an American psychologist, behaviorist, inventor, and social philosopher. [2][3][4][5] He was the Edgar Pierce Professor of Psychology at Harvard University from 1958 until his retirement in ...
Machine learningand data mining. Reinforcement learning (RL) is an interdisciplinary area of machine learning and optimal control concerned with how an intelligent agent ought to take actions in a dynamic environment in order to maximize the cumulative reward. Reinforcement learning is one of three basic machine learning paradigms, alongside ...
Reinforcement sensitivity theory. Reinforcement sensitivity theory (RST) proposes three brain-behavioral systems that underlie individual differences in sensitivity to reward, punishment, and motivation. While not originally defined as a theory of personality, the RST has been used to study and predict anxiety, impulsivity, and extraversion. [1]
Clark Leonard Hull (May 24, 1884 – May 10, 1952) was an American psychologist who sought to explain learning and motivation by scientific laws of behavior. Hull is known for his debates with Edward C. Tolman. He is also known for his work in drive theory. Hull spent the mature part of his career at Yale University, where he was recruited by ...
In applied behavior analysis, the Premack principle is sometimes known as "grandma's rule", which states that making the opportunity to engage in high-frequency behavior contingent upon the occurrence of low-frequency behavior will function as a reinforcer for the low-frequency behavior. [6] In other words, an individual must "first" engage in ...
e. In machine learning, reinforcement learning from human feedback (RLHF) is a technique to align an intelligent agent with human preferences. It involves training a reward model to represent preferences, which can then be used to train other models through reinforcement learning. In classical reinforcement learning, an intelligent agent's goal ...