Ads
related to: reinforcement learning ppt presentation powerpointofficetimeline.com has been visited by 10K+ users in the past month
Search results
Results From The WOW.Com Content Network
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 ...
This criticism of rapid learning development focuses on the idea that the richness of an interaction with students in the classroom is not encapsulated in a PowerPoint presentation file. Consequently, an online course is a mere passive information presentation but not a training activity with questions, workshops, problems.
Various techniques exist to train policies to solve tasks with deep reinforcement learning algorithms, each having their own benefits. At the highest level, there is a distinction between model-based and model-free reinforcement learning, which refers to whether the algorithm attempts to learn a forward model of the environment dynamics.
Q-learning is a model-free reinforcement learning algorithm that teaches an agent to assign values to each action it might take, conditioned on the agent being in a particular state. It does not require a model of the environment (hence "model-free"), and it can handle problems with stochastic transitions and rewards without requiring adaptations.
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 .
importance of these preferences to health behaviors, a recent meta-analysis of reinforcement contingency management (in which people are paid for improving health behaviors) found that the single most important determinant of effect size was whether behavior-contingent rewards