Policy learning is the increased understanding that occurs when policymakers compare one set of policy problems to others within their own or in other...

Reinforcement learning is one of the three basic machine learning paradigms, alongside supervised learning and unsupervised learning. Q-learning at its simplest...

Deep reinforcement learning (deep RL) is a subfield of machine learning that combines reinforcement learning (RL) and deep learning. RL considers the problem...

requiring adaptations. For any finite Markov decision process, Q-learning finds an optimal policy in the sense of maximizing the expected value of the total...

reinforcement learning. In classical reinforcement learning, an intelligent agent's goal is to learn a function that guides its behavior, called a policy. This...

Proximal policy optimization (PPO) is a reinforcement learning algorithm for training an intelligent agent's decision function to accomplish difficult...

Machine learning (ML) is a field of study in artificial intelligence concerned with the development and study of statistical algorithms that can learn...

MC learning algorithm is essentially an important branch of generalized policy iteration, which has two periodically alternating steps, i.e., policy evaluation...

controversial, the policy called for the use and learning of Hindi to be encouraged uniformly to promote a common language for all Indians. The policy also encouraged...

1177/0002716204272652. S2CID 154759501. Meseguer, Covadonga (2005). "Policy Learning, Policy Diffusion, and the Making of a New Order". The Annals of the American...

incremental learning policies in the field of online machine learning. Using active learning allows for faster development of a machine learning algorithm...

the latter one is more used in Learning Theory. A policy that maximizes the function above is called an optimal policy and is usually denoted π ∗ {\displaystyle...

In statistics and machine learning, ensemble methods use multiple learning algorithms to obtain better predictive performance than could be obtained from...

system of India. The new policy replaces the previous National Policy on Education, 1986. Shortly after the release of the policy, the government clarified...

researchers have expanded their focus to include informal learning environments, instructional methods, policy innovations, and the design of curricula. As an emerging...

state of the MDP. A positive learning rate α {\displaystyle \alpha } is chosen. We then repeatedly evaluate the policy π {\displaystyle \pi } , obtain...

(distributed learning, e-learning, m-learning, online learning, virtual classroom, etc.) are used roughly synonymously with distance education. E-learning has...

non-formal learning contexts with a lifelong learning approach, and to ensure that data are collected on the most excluded. Education policy in Brazil...

In machine learning, diffusion models, also known as diffusion probabilistic models or score-based generative models, are a class of latent variable generative...

policy to allow authors to self-archive their papers online after peer-review. J.R. Quinlan (1986). "Induction of Decision Trees". Machine Learning....

(BC) is the most basic form of imitation learning. Essentially, it uses supervised learning to train a policy π θ {\displaystyle \pi _{\theta }} such that...

Learning disability, learning disorder, or learning difficulty (British English) is a condition in the brain that causes difficulties comprehending or...

Minerva: A Review of Science, Learning and Policy is a quarterly peer-reviewed academic journal covering the sociological study of scientific knowledge...

suite of model-free off-policy reinforcement learning algorithms, tailored for learning decision-making or control policies in complex systems with continuous...

developed policies for life-long learning which focus strongly on the need to identify, assess and certify non-formal and informal learning, particularly...

Blended learning or hybrid learning, also known as technology-mediated instruction, web-enhanced instruction, or mixed-mode instruction, is an approach...

transparency, and accountability; policy with clear objectives, evaluation techniques, and exit strategies; policy learning and policy experimentation; green rent...

(SARSA) is an algorithm for learning a Markov decision process policy, used in the reinforcement learning area of machine learning. It was proposed by Rummery...

encompasses several domains including learning theory, computer-based training, online learning, and m-learning where mobile technologies are used. The...

Lifelong learning is the "ongoing, voluntary, and self-motivated" pursuit of learning for either personal or professional reasons. Lifelong learning is important...