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Markov decision process

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Mathematical model for sequential decision making under uncertaintyA Markov decision process (MDP) is a mathematical model for sequential decision making when outcomes are uncertain. It is a type of stochastic decision process, and is often solved using the methods of stochastic dynamic programming. Originating from operations research in the 1950s, MDPs have since gained recognition in a variety of fields, including ecology, economics, healthcare, telecommunications and reinforcement learning.

Reinforcement learningReinforcement learningIn machine learning and optimal control, reinforcement learning (RL) (also known as approximate dynamic programming) is 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 learning.Stochastic dynamic programmingStochastic dynamic programming1957 technique for modelling problems of decision making under uncertaintyOriginally introduced by Richard E. Bellman in (Bellman 1957), stochastic dynamic programming (SDP) is a technique for modelling and solving problems of decision making under uncertainty. Closely related to stochastic programming and dynamic programming, stochastic dynamic programming represents the problem under scrutiny in the form of a Bellman equation.Sequential decision makingSequential decision making is a concept in control theory and operations research, which involves making a series of decisions over time to optimize an objective function, such as maximizing cumulative rewards or minimizing costs. In this framework, each decision influences subsequent choices and system outcomes, taking into account the current state, available actions, and the probabilistic nature of state transitions.Operations researchOperations researchOperations research (British English: operational research), often shortened to the initialismOR, is a branch of applied mathematics that deals with the development and application of analytical methods to improve management and decision-making. The term management science is occasionally used as a synonym.Artificial intelligenceArtificial intelligenceIntelligence in machinesArtificial intelligence (AI) is the capability of computational systems to perform tasks typically associated with human intelligence, such as learning, reasoning, problem-solving, perception, and decision-making.CausalityCausalityHow one process influences anotherCausality is an influence by which one event, process, state, or subject (i.e., a cause) contributes to the production of another event, process, state, or object (i.e., an effect) where the cause is at least partly responsible for the effect, and the effect is at least partly dependent on the cause. The cause of something may also be described as the reason behind the event or process.Outcome (probability)Outcome (probability)In probability theory, an outcome is a possible result of an experiment or trial. Each possible outcome of a particular experiment is a unique random element, and different outcomes are mutually exclusive (only one outcome will occur on each trial of the experiment). All of the possible outcomes of an experiment form the elements of a sample space.Health careHealth careHealth care, or healthcare, is the improvement or maintenance of health via the prevention, diagnosis, treatment, or cure of disease, illness, injury, and other physical and mental impairments in people. Health care is delivered by health professionals and allied health fields. Medicine, dentistry, pharmacy, midwifery, nursing, optometry, audiology, psychology, occupational therapy, physical therapy, athletic training, and other health professions all constitute health care.StochasticStochasticStochasticity is the property of being well-described by a randomprobability distribution. Stochasticity and randomness are technically distinct concepts: stochasticity refers to a modeling approach, while randomness describes phenomena. These terms are often used interchangeably. In probability theory, the formal concept of a stochastic process is also referred to as a random process.EconomicsEconomicsEconomics () is a social science that studies the production, distribution, and consumption of goods and services. Economics focuses on the behaviour and interactions of economic agents and how economies work. Microeconomics analyses what is viewed as the basic elements of economies, including individual agents and markets, their interactions, and the outcomes of those interactions. Individual agents may include households, firms, buyers, and sellers.EcologyEcologyEcology (from Ancient Greek οἶκος (oîkos) 'house' and -λογία (-logía) 'study of') is the natural science which studies the interactions between organisms and their environments. Ecology considers organisms at the community, ecosystem, and biosphere levels. Ecology overlaps with the sciences of biogeography, evolutionary biology, genetics, and ethology.TelecommunicationsTelecommunicationsTelecommunication, often used in its plural form or abbreviated as telecom, is the transmission of information over a distance using electrical or electronic means, typically through cables, radio waves, or other communication technologies. These means of transmission may be divided into communication channels for multiplexing, allowing for a single medium to transmit several concurrent communication sessions.

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