The University of Essex is a public research university in Essex, England. It was established in 1963, welcomed its first students in 1964 and received its royal charter in 1965. Essex's motto, ’Thought the harder, heart the keener’, is adapted from the Anglo-Saxon poem The Battle of Maldon.
The Chinese University of Hong Kong (CUHK) is a public research university in Shatin, Hong Kong formally established in 1963 by a charter granted by the Legislative Council of Hong Kong. It is the territory's second oldest university and was founded as a federation of three existing colleges – Chung Chi College, New Asia College and United College – the oldest of which was founded in 1949.
In computer science, artificial intelligence (AI), sometimes called machine intelligence, is intelligence demonstrated by machines, in contrast to the natural intelligence displayed by humans. Leading AI textbooks define the field as the study of "intelligent agents": any device that perceives its environment and takes actions that maximize its chance of successfully achieving its goals. Colloquially, the term "artificial intelligence" is often used to describe machines that mimic "cognitive" functions that humans associate with the human mind, such as "learning" and "problem solving".
Computational finance is a branch of applied computer science that deals with problems of practical interest in finance. Some slightly different definitions are the study of data and algorithms currently used in finance and the mathematics of computer programs that realize financial models or systems.
In artificial intelligence and operations research, constraint satisfaction is the process of finding a solution to a set of constraints that impose conditions that the variables must satisfy. A solution is therefore a set of values for the variables that satisfies all constraints—that is, a point in the feasible region.
The International Standard Book Number (ISBN) is a numeric commercial book identifier which is intended to be unique. Publishers purchase ISBNs from an affiliate of the International ISBN Agency.
In artificial intelligence, an evolutionary algorithm (EA) is a subset of evolutionary computation, a generic population-based metaheuristic optimization algorithm. An EA uses mechanisms inspired by biological evolution, such as reproduction, mutation, recombination, and selection. Candidate solutions to the optimization problem play the role of individuals in a population, and the fitness function determines the quality of the solutions. Evolution of the population then takes place after the repeated application of the above operators.
In computer science, evolutionary computation is a family of algorithms for global optimization inspired by biological evolution, and the subfield of artificial intelligence and soft computing studying these algorithms. In technical terms, they are a family of population-based trial and error problem solvers with a metaheuristic or stochastic optimization character.
Bio-inspired computing, short for biologically inspired computing, is a field of study which seeks to solve computer science problems using models of biology. It relates to connectionism, social behavior, and emergence. Within computer science, bio-inspired computing relates to artificial intelligence and machine learning. Bio-inspired computing is a major subset of natural computation.
Neuroevolution, or neuro-evolution, is a form of artificial intelligence that uses evolutionary algorithms to generate artificial neural networks (ANN), parameters, topology and rules. It is most commonly applied in artificial life, general game playing and evolutionary robotics. The main benefit is that neuroevolution can be applied more widely than supervised learning algorithms, which require a syllabus of correct input-output pairs. In contrast, neuroevolution requires only a measure of a network's performance at a task. For example, the outcome of a game can be easily measured without providing labeled examples of desired strategies. Neuroevolution is commonly used as part of the reinforcement learning paradigm, and it can be contrasted with conventional deep learning techniques that use gradient descent on a neural network with a fixed topology.
Evolutionary robotics (ER) is a methodology that uses evolutionary computation to develop controllers and/or hardware for autonomous robots. Algorithms in ER frequently operate on populations of candidate controllers, initially selected from some distribution. This population is then repeatedly modified according to a fitness function. In the case of genetic algorithms, a common method in evolutionary computation, the population of candidate controllers is repeatedly grown according to crossover, mutation and other GA operators and then culled according to the fitness function. The candidate controllers used in ER applications may be drawn from some subset of the set of artificial neural networks, although some applications use collections of "IF THEN ELSE" rules as the constituent parts of an individual controller. It is theoretically possible to use any set of symbolic formulations of a control law as the space of possible candidate controllers. Artificial neural networks can also be used for robot learning outside the context of evolutionary robotics. In particular, other forms of reinforcement learning can be used for learning robot controllers.
The expression computational intelligence (CI) usually refers to the ability of a computer to learn a specific task from data or experimental observation. Even though it is commonly considered a synonym of soft computing, there is still no commonly accepted definition of computational intelligence.
In artificial intelligence, artificial immune systems (AIS) are a class of computationally intelligent, rule-based machine learning systems inspired by the principles and processes of the vertebrate immune system. The algorithms are typically modeled after the immune system's characteristics of learning and memory for use in problem-solving.
In computer science and operations research, a memetic algorithm (MA) is an extension of the traditional genetic algorithm. It uses a local search technique to reduce the likelihood of the premature convergence.
Dr. Lawrence Jerome Fogel was a pioneer in evolutionary computation and human factors analysis. He is known as the inventor of active noise cancellation and the father of evolutionary programming. His scientific career spanned nearly six decades and included electrical engineering, aerospace engineering, communication theory, human factors research, information processing, cybernetics, biotechnology, artificial intelligence, and computer science.
Guided Local Search is a metaheuristic search method. A meta-heuristic method is a method that sits on top of a local search algorithm to change its behavior.
Riccardo Poli is a Professor in the Department of Computing and Electronic Systems of the University of Essex. His work has centered on genetic programming.
The IEEE Computational Intelligence Society is a professional society of the Institute of Electrical and Electronics Engineers (IEEE) focussing on "the theory, design, application, and development of biologically and linguistically motivated computational paradigms emphasizing neural networks, connectionist systems, genetic algorithms, evolutionary programming, fuzzy systems, and hybrid intelligent systems in which these paradigms are contained".
Sheri Marina Markose is a computational economist. She is a professor of Economics at the University of Essex, where she holds a personal chair since 2006. She is the founding director (2002-2009) of the Centre for Computational Finance and Economic Agents (CCFEA) at Essex. At CCFEA, with the support of the then Vice Chancellor, Ivor Crewe, she pioneered multi-disciplinary research as well as PhD and Masters programs, which include Agent-based computational economics, financial market modelling with extreme events and markets as complex adaptive systems.
Design Automation usually refers to electronic design automation, or Design Automation which is a Product Configurator. Extending Computer-Aided Design (CAD), automated design and Computer-Automated Design (CAutoD) are more concerned with a broader range of applications, such as automotive engineering, civil engineering, composite material design, control engineering, dynamic system identification and optimization, financial systems, industrial equipment, mechatronic systems, steel construction, structural optimisation, and the invention of novel systems.
The School of Computer Science and Electronic Engineering at the University of Essex is an academic department that focuses on educating and researching into Computer Science and Electronic Engineering specific matters. It was formed by the merger of two departments, notable for being amongst the first in England in their fields, the Department of Electronic Systems Engineering(1966) and the Department of Computer Science (1966).
The Genetic and Evolutionary Computation Conference (GECCO) is the premier conference in the area of genetic and evolutionary computation. GECCO has been held every year since 1999, when it was first established as a recombination of the International Conference on Genetic Algorithms (ICGA) and the Annual Genetic Programming Conference (GP).
This glossary of artificial intelligence terms is about artificial intelligence, its sub-disciplines, and related fields.
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