|
Memetic Computing
{{Cleanup, reason=The article is full of incorrect capitalization., date=May 2024 Memetic computing is a novel computational paradigm that incorporates the notion of meme(s) as basic units of transferable information encoded in computational representations for boosting the performance of artificial evolutionary systems in the domain of search and optimization. The term memetic computing is often unassumingly misinterpreted to mean the same thing as memetic algorithms (MAs) that typically hybridize population-based global search algorithms with one or more local search schemes. Notably, memetic computing offers a much broader scope, perpetuating the idea of memes into concepts that pave the way towards simultaneous problem learning and optimization approaches. Methods There are two different methods that describe the history and rise of memetics in computing. These are human-crafted memes and machine-crafted memes. Human-crafted memes One of the most widely recognised inst ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Meme
A meme (; ) is an idea, behavior, or style that Mimesis, spreads by means of imitation from person to person within a culture and often carries symbolic meaning representing a particular phenomenon or theme. A meme acts as a unit for carrying culture, cultural ideas, symbols, or practices, that can be transmitted from one mind to another through writing, speech, gestures, rituals, or other imitable phenomena with a mimicked theme. Supporters of the concept regard memes as cultural analogues to genes in that they Self-replication, self-replicate, mutate, and respond to natural selection, selective pressures. In popular language, a meme may refer to an Internet meme, typically an image, that is remixed, copied, and circulated in a shared cultural experience online. Proponents theorize that memes are a viral phenomenon that may evolve by natural selection in a manner analogous to that of evolution, biological evolution. Memes do this through processes analogous to those of genetic ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Optimization
Mathematical optimization (alternatively spelled ''optimisation'') or mathematical programming is the selection of a best element, with regard to some criteria, from some set of available alternatives. It is generally divided into two subfields: discrete optimization and continuous optimization. Optimization problems arise in all quantitative disciplines from computer science and engineering to operations research and economics, and the development of solution methods has been of interest in mathematics for centuries. In the more general approach, an optimization problem consists of maxima and minima, maximizing or minimizing a Function of a real variable, real function by systematically choosing Argument of a function, input values from within an allowed set and computing the Value (mathematics), value of the function. The generalization of optimization theory and techniques to other formulations constitutes a large area of applied mathematics. Optimization problems Opti ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Memetic Algorithms
In computer science Computer science is the study of computation, information, and automation. Computer science spans Theoretical computer science, theoretical disciplines (such as algorithms, theory of computation, and information theory) to Applied science, ... and operations research, a memetic algorithm (MA) is an extension of an evolutionary algorithm (EA) that aims to accelerate the evolutionary search for the optimum. An EA is a metaheuristic that reproduces the basic principles of biological evolution as a computer algorithm in order to solve challenging Optimization problem, optimization or planning tasks, at least Approximation, approximately. An MA uses one or more suitable heuristics or Local search (optimization), local search techniques to improve the quality of solutions generated by the EA and to speed up the search. The effects on the Premature convergence, reliability of finding the global optimum depend on both the use case and the Memetic algorithm#Som ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Gradient Descent
Gradient descent is a method for unconstrained mathematical optimization. It is a first-order iterative algorithm for minimizing a differentiable multivariate function. The idea is to take repeated steps in the opposite direction of the gradient (or approximate gradient) of the function at the current point, because this is the direction of steepest descent. Conversely, stepping in the direction of the gradient will lead to a trajectory that maximizes that function; the procedure is then known as ''gradient ascent''. It is particularly useful in machine learning for minimizing the cost or loss function. Gradient descent should not be confused with local search algorithms, although both are iterative methods for optimization. Gradient descent is generally attributed to Augustin-Louis Cauchy, who first suggested it in 1847. Jacques Hadamard independently proposed a similar method in 1907. Its convergence properties for non-linear optimization problems were first studied by Has ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Memetics
Memetics is a theory of the evolution of culture based on Darwinian principles with the meme as the unit of culture. The term "meme" was coined by biologist Richard Dawkins in his 1976 book '' The Selfish Gene'', to illustrate the principle that he later called " Universal Darwinism". All evolutionary processes depend on information being copied, varied, and selected, a process also known as variation with selective retention. The conveyor of the information being copied is known as the replicator, with the gene functioning as the replicator in biological evolution. Dawkins proposed that the same process drives cultural evolution, and he called this second replicator the "meme," citing examples such as musical tunes, catchphrases, fashions, and technologies. Like genes, memes are selfish replicators and have causal efficacy; in other words, their properties influence their chances of being copied and passed on. Some succeed because they are valuable or useful to their human hosts ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Memetic Algorithm
In computer science and operations research, a memetic algorithm (MA) is an extension of an evolutionary algorithm (EA) that aims to accelerate the evolutionary search for the optimum. An EA is a metaheuristic that reproduces the basic principles of biological evolution as a computer algorithm in order to solve challenging optimization or planning tasks, at least approximately. An MA uses one or more suitable heuristics or local search techniques to improve the quality of solutions generated by the EA and to speed up the search. The effects on the reliability of finding the global optimum depend on both the use case and the design of the MA. Memetic algorithms represent one of the recent growing areas of research in evolutionary computation. The term MA is now widely used as a synergy of evolutionary or any population-based approach with separate individual learning or local improvement procedures for problem search. Quite often, MAs are also referred to in the literature as ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
