Search results
Results from the WOW.Com Content Network
Traditional lecturing, in which an instructor speaks uninterrupted for the majority of the class, is often less effective than active student response techniques. Without active participation from students and contingent positive reinforcement for correct responses, traditional lecturing does not reinforce desired behaviors.
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 ...
Differential reinforcement of low response rate (DRL) – Used to encourage low rates of responding. It is like an interval schedule, except that premature responses reset the time required between behavior. Differential reinforcement of high rate (DRH) – Used to increase high rates of responding. It is like an interval schedule, except that ...
Reinforcement learning is a subset of machine learning. It enables an agent to learn through the consequences of actions in a specific environment. Reinforcement learning is a behavioral learning ...
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 .
Proponents argue that classroom learning activities must build upon students' prior knowledge and teachers need to allocate time for practice. Advocates argue that teachers must continuously assess student learning against clearly defined standards and goals, and student input into the assessment process is integral. [9] [10] [11]
In multi-agent reinforcement learning experiments, researchers try to optimize the performance of a learning agent on a given task, in cooperation or competition with one or more agents. These agents learn by trial-and-error, and researchers may choose to have the learning algorithm play the role of two or more of the different agents.
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]