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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 .
Just as "reward" was commonly used to alter behavior long before "reinforcement" was studied experimentally, the Premack principle has long been informally understood and used in a wide variety of circumstances. An example is a mother who says, "You have to finish your vegetables (low frequency) before you can eat any ice cream (high frequency)."
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 ...
Such rules could also be the result of optimization, realized through use of AI methods (such as Q-learning and other reinforcement learning techniques). [ 3 ] As part of non-equilibrium economics , [ 4 ] the theoretical assumption of mathematical optimization by agents in equilibrium is replaced by the less restrictive postulate of agents with ...
In the context of machine learning, the exploration–exploitation tradeoff is fundamental in reinforcement learning (RL), a type of machine learning that involves training agents to make decisions based on feedback from the environment. Crucially, this feedback may be incomplete or delayed. [4]
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).
The ERN is a sharp negative going signal which begins about the same time an incorrect motor response begins, (response locked event-related potential), and typically peaks from 80 to 150 milliseconds (ms) after the erroneous response begins (or 40–80 ms after the onset of electromyographic activity).
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".