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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 .
The standard definition of behavioral reinforcement has been criticized as circular, since it appears to argue that response strength is increased by reinforcement, and defines reinforcement as something that increases response strength (i.e., response strength is increased by things that increase response strength).
Knowledge of results is a term in the psychology of learning. [1] [2]: 619 A psychology dictionary defines it as feedback of information: "(a) to a subject about the correctness of [their] responses; (b) a student about success or failure in mastering material, or (c) a client in psychotherapy about progress".
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 ]
Skinner described operant conditioning as strengthening behaviour through reinforcement. Reinforcement can consist of positive reinforcement, in which a desirable stimulus is added; negative reinforcement, in which an undesirable stimulus is taken away; positive punishment, in which an undesirable stimulus is added; and negative punishment, in which a desirable stimulus is taken away. [7]
Social learning theory is a theory of social behavior that proposes that new behaviors can be acquired by observing and imitating others. It states that learning is a cognitive process that takes place in a social context and can occur purely through observation or direct instruction, even in the absence of motor reproduction or direct reinforcement. [1]
Reinforcement learning (RL) is an interdisciplinary area of machine learning and optimal control concerned with how an intelligent agent should take actions in a dynamic environment in order to maximize a reward signal. Reinforcement learning is one of the three basic machine learning paradigms, alongside supervised learning and unsupervised ...
Industrial and organizational psychology focuses on the corporate world to help the function of the work flow for organizations and their relationships with employees. This helps increase job satisfaction and work goals by using surveys and reinforcement with a reward system between employee and employer.