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Adaptive System
An adaptive system is a set of interacting or interdependent entities, real or abstract, forming an integrated whole that together are able to respond to environmental changes or changes in the interacting parts, in a way analogous to either continuous physiological homeostasis or evolutionary adaptation in biology. Feedback loops represent a key feature of adaptive systems, such as ecosystems and individual organisms; or in the human world, communities, organizations, and families. Adaptive systems can be organized into a hierarchy. Artificial adaptive systems include robots with control systems that utilize negative feedback to maintain desired states. The law of adaptation The law of adaptation may be stated informally as: Formally, the law can be defined as follows: Given a system S, we say that a physical event E is a stimulus for the system S if and only if the probability P(S \rightarrow S', E) that the system suffers a change or be perturbed (in its elements or i ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Homeostasis
In biology, homeostasis (British English, British also homoeostasis; ) is the state of steady internal physics, physical and chemistry, chemical conditions maintained by organism, living systems. This is the condition of optimal functioning for the organism and includes many variables, such as body temperature and fluid balance, being kept within certain pre-set limits (homeostatic range). Other variables include the pH of extracellular fluid, the concentrations of sodium, potassium, and calcium ions, as well as the blood sugar level, and these need to be regulated despite changes in the environment, diet, or level of activity. Each of these variables is controlled by one or more regulators or homeostatic mechanisms, which together maintain life. Homeostasis is brought about by a natural resistance to change when already in optimal conditions, and equilibrium is maintained by many regulatory mechanisms; it is thought to be the central motivation for all organic action. All home ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Cybernetic
Cybernetics is the transdisciplinary study of circular causal processes such as feedback and recursion, where the effects of a system's actions (its outputs) return as inputs to that system, influencing subsequent action. It is concerned with general principles that are relevant across multiple contexts, including in engineering, ecological, economic, biological, cognitive and social systems and also in practical activities such as designing, learning, and managing. Cybernetics' transdisciplinary character has meant that it intersects with a number of other fields, leading to it having both wide influence and diverse interpretations. The field is named after an example of circular causal feedback—that of steering a ship (the ancient Greek κυβερνήτης (''kybernḗtēs'') refers to the person who steers a ship). In steering a ship, the position of the rudder is adjusted in continual response to the effect it is observed as having, forming a feedback loop through whi ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Neural Adaptation
Neural adaptation or sensory adaptation is a gradual decrease over time in the responsiveness of the sensory system to a constant stimulus. It is usually experienced as a change in the stimulus. For example, if a hand is rested on a table, the table's surface is immediately felt against the skin. Subsequently, however, the sensation of the table surface against the skin gradually diminishes until it is virtually unnoticeable. The sensory neurons that initially respond are no longer stimulated to respond; this is an example of neural adaptation. All sensory and neural systems have a form of adaptation to constantly detect changes in the environment. Neural receptor cells that process and receive stimulation go through constant changes for mammals and other living organisms to sense vital changes in their environment. Some key players in several neural systems include Ca2+ions (see Calcium in biology) that send negative feedback in second messenger pathways that allow the neural r ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Learning
Learning is the process of acquiring new understanding, knowledge, behaviors, skills, value (personal and cultural), values, Attitude (psychology), attitudes, and preferences. The ability to learn is possessed by humans, non-human animals, and some machine learning, machines; there is also evidence for some kind of learning in certain plants. Some learning is immediate, induced by a single event (e.g. being burned by a Heat, hot stove), but much skill and knowledge accumulate from repeated experiences. The changes induced by learning often last a lifetime, and it is hard to distinguish learned material that seems to be "lost" from that which cannot be retrieved. Human learning starts at birth (it might even start before) and continues until death as a consequence of ongoing interactions between people and their environment. The nature and processes involved in learning are studied in many established fields (including educational psychology, neuropsychology, experimental psycho ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Genetic Algorithms
In computer science and operations research, a genetic algorithm (GA) is a metaheuristic inspired by the process of natural selection that belongs to the larger class of evolutionary algorithms (EA). Genetic algorithms are commonly used to generate high-quality solutions to optimization and search problems via biologically inspired operators such as selection, crossover, and mutation. Some examples of GA applications include optimizing decision trees for better performance, solving sudoku puzzles, hyperparameter optimization, and causal inference. Methodology Optimization problems In a genetic algorithm, a population of candidate solutions (called individuals, creatures, organisms, or phenotypes) to an optimization problem is evolved toward better solutions. Each candidate solution has a set of properties (its chromosomes or genotype) which can be mutated and altered; traditionally, solutions are represented in binary as strings of 0s and 1s, but other encodi ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Gene Expression Programming
Gene expression programming (GEP) in computer programming is an evolutionary algorithm that creates computer programs or models. These computer programs are complex tree structures that learn and adapt by changing their sizes, shapes, and composition, much like a living organism. And like living organisms, the computer programs of GEP are also encoded in simple linear chromosomes of fixed length. Thus, GEP is a Genotype–phenotype distinction, genotype–phenotype system, benefiting from a simple genotype, genome to keep and transmit the genetic information and a complex phenotype to explore the environment and adapt to it. Background Evolutionary algorithms use populations of individuals, select individuals according to fitness, and introduce genetic variation using one or more genetic operators. Their use in artificial computational systems dates back to the 1950s where they were used to solve optimization problems (e.g. Box 1957 and Friedman 1959). But it was with the introdu ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Gaia Hypothesis
The Gaia hypothesis (), also known as the Gaia theory, Gaia paradigm, or the Gaia principle, proposes that living organisms interact with their Inorganic compound, inorganic surroundings on Earth to form a Synergy, synergistic and Homeostasis, self-regulating complex system that helps to maintain and perpetuate the conditions for life on the planet. The Gaia hypothesis was formulated by the chemist James Lovelock and co-developed by the microbiologist Lynn Margulis in the 1970s. Following the suggestion by his neighbour, novelist William Golding, Lovelock named the hypothesis after Gaia, the primordial deity who personified the Earth in Greek mythology. In 2006, the Geological Society of London awarded Lovelock the Wollaston Medal in part for his work on the Gaia hypothesis. Topics related to the hypothesis include how the biosphere and the evolution of organisms affect the stability of global temperature, salinity of seawater, atmospheric oxygen levels, the maintenance of a hyd ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Ecosystems
An ecosystem (or ecological system) is a system formed by Organism, organisms in interaction with their Biophysical environment, environment. The Biotic material, biotic and abiotic components are linked together through nutrient cycles and energy flows. Ecosystems are controlled by external and internal Environmental factor, factors. External factors—including climate—control the ecosystem's structure, but are not influenced by it. By contrast, internal factors control and are controlled by ecosystem processes; these include decomposition, the types of species present, root competition, shading, disturbance, and succession. While external factors generally determine which Resource (biology), resource inputs an ecosystem has, their availability within the ecosystem is controlled by internal factors. Ecosystems are wikt:dynamic, dynamic, subject to periodic disturbances and always in the process of recovering from past disturbances. The tendency of an ecosystem to remain clo ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Diffusion Of Innovations
Diffusion of innovations is a theory that seeks to explain how, why, and at what rate new ideas and technology spread. The theory was popularized by Everett Rogers in his book ''Diffusion of Innovations'', first published in 1962. Rogers argues that diffusion is the process by which an innovation is communicated through certain channels over time among the participants in a social system. The origins of the diffusion of innovations theory are varied and span multiple disciplines. Rogers proposes that five main elements influence the spread of a new idea: the innovation itself, adopters, communication channels, time, and a social system. This process relies heavily on social capital. The innovation must be widely adopted in order to self-sustain. Within the rate of adoption, there is a point at which an innovation reaches critical mass. In 1989, management consultants working at the consulting firm Regis McKenna, Inc. theorized that this point lies at the boundary between the ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Complex Adaptive System
A complex adaptive system (CAS) is a system that is ''complex'' in that it is a dynamic network of interactions, but the behavior of the ensemble may not be predictable according to the behavior of the components. It is '' adaptive'' in that the individual and collective behavior mutate and self-organize corresponding to the change-initiating micro-event or collection of events. It is a "complex macroscopic collection" of relatively "similar and partially connected micro-structures" formed in order to adapt to the changing environment and increase their survivability as a macro-structure. The Complex Adaptive Systems approach builds on replicator dynamics. The study of complex adaptive systems, a subset of nonlinear dynamical systems, is an interdisciplinary matter that attempts to blend insights from the natural and social sciences to develop system-level models and insights that allow for heterogeneous agents, phase transition, and emergent behavior. Overview The term ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Artificial Neural Network
In machine learning, a neural network (also artificial neural network or neural net, abbreviated ANN or NN) is a computational model inspired by the structure and functions of biological neural networks. A neural network consists of connected units or nodes called '' artificial neurons'', which loosely model the neurons in the brain. Artificial neuron models that mimic biological neurons more closely have also been recently investigated and shown to significantly improve performance. These are connected by ''edges'', which model the synapses in the brain. Each artificial neuron receives signals from connected neurons, then processes them and sends a signal to other connected neurons. The "signal" is a real number, and the output of each neuron is computed by some non-linear function of the sum of its inputs, called the '' activation function''. The strength of the signal at each connection is determined by a ''weight'', which adjusts during the learning process. Typically, ne ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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Adaptive Immune System
The adaptive immune system (AIS), also known as the acquired immune system, or specific immune system is a subsystem of the immune system that is composed of specialized cells, organs, and processes that eliminate pathogens specifically. The acquired immune system is one of the two main immunity strategies found in vertebrates (the other being the innate immune system). Like the innate system, the adaptive immune system includes both humoral immunity components and cell-mediated immunity components and destroys invading pathogens. Unlike the innate immune system, which is pre-programmed to react to common broad categories of pathogen, the adaptive immune system is highly specific to each particular pathogen the body has encountered. Adaptive immunity creates immunological memory after an initial response to a specific pathogen, and leads to an enhanced response to future encounters with that pathogen. Antibodies are a critical part of the adaptive immune system. Adaptive im ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |