💡 Words with a Similar Meaning to "Reinforcement learning"
Found via reverse dictionary — words that share a conceptual meaning.
| Word | Definition |
|---|---|
| deep reinforcement learning | (deep RL) a subfield of machine learning that combines reinforcement learning and deep learning. |
| algorithmic game theory | an area in the intersection of game theory and computer science, with the objective of understanding and design of algorithms in strategic environments. |
| intrinsic motivationnoun | (psychology) The incentive to undertake an activity based on the expected enjoyment of the activity itself, rather than external benefits that might result. |
| feature learning | In machine learning, feature learning or representation learning is a set of techniques that allow a system to automatically discover the representations needed for feature detection or classification from raw data. |
| evolutionary algorithm | In computational intelligence, an evolutionary algorithm is a subset of evolutionary computation, a generic population-based metaheuristic optimization algorithm. |
| temporal difference learning | Temporal difference learning refers to a class of model-free reinforcement learning methods which learn by bootstrapping from the current estimate of the value function. |
| constraint satisfaction | In artificial intelligence and operations research, constraint satisfaction is the process of finding a solution through |
| supervised learning | In machine learning, supervised learning is a paradigm where a model is trained using input objects (e.g. a vector of predictor variables) and desired output values (also known as a supervisory signal), which are often human-made labels. |
| empowermentnoun | The achievement of political, social or economic power by an individual or group. |
| empirical risk minimization | In statistical learning theory, the principle of empirical risk minimization defines a family of learning algorithms based on evaluating performance over a known and fixed dataset. |
| q-learningnoun | (computing theory) A model-free reinforcement learning algorithm to learn a policy telling an agent what action to take under what circumstances. |
| connectionismnoun | (cognitive science) Any of several fields of psychology that model brain processes in terms of interconnected networks. |
| particle swarm optimization | In computational science, particle swarm optimization is a computational method that optimizes a problem by iteratively trying to improve a candidate solution with regard to a given measure of quality. |
| applied behavior analysis | Applied behavior analysis, also referred to as behavioral engineering, is a psychological discipline that utilizes the principles of learning based upon respondent and operant conditioning to change socially significant behavior. |
| diagnosisnoun | (medicine, countable, uncountable) The process of, or an instance of, identification of the nature and cause of a medical condition or illness. |
| differential evolution | In evolutionary computation, differential evolution is a method that optimizes a problem by iteratively trying to improve a candidate solution with regard to a given measure of quality. |
| neuroeconomicsnoun | A combination of neuroscience, economics and psychology used to study the decision-making process. |
| learning rate | In machine learning and statistics, the learning rate is a tuning parameter in an optimization algorithm that determines the step size at each iteration while moving toward a minimum of a loss function. |
| probabilistic neural network | A probabilistic neural network is a feedforward neural network, which is widely used in classification and pattern recognition problems. |
| restricted boltzmann machine | A restricted Boltzmann machine (also called a restricted Sherrington–Kirkpatrick model with external field or restricted stochastic Ising–Lenz–Little model) is a generative stochastic artificial neural network that can learn a probability distribution over its set of inputs. |
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