Systems theory is the transdisciplinary study of systems, i.e. cohesive groups of interrelated, interdependent components that can be natural or artificial. Every system has causal boundaries, is influenced by its context, defined by its structure, function and role, and expressed through its relations with other systems. A system is "more than the sum of its parts" when it expresses synergy or emergent behavior.
Computational neuroscience is a branch of neuroscience which employs mathematics, computer science, theoretical analysis and abstractions of the brain to understand the principles that govern the development, structure, physiology and cognitive abilities of the nervous system.
Systems science, also referred to as systems research, or, simply, systems, is a transdisciplinary field that is concerned with understanding simple and complex systems in nature and society, which leads to the advancements of formal, natural, social, and applied attributions throughout engineering, technology and science, itself.
Developmental robotics (DevRob), sometimes called epigenetic robotics, is a scientific field which aims at studying the developmental mechanisms, architectures and constraints that allow lifelong and open-ended learning of new skills and new knowledge in embodied machines. As in human children, learning is expected to be cumulative and of progressively increasing complexity, and to result from self-exploration of the world in combination with social interaction. The typical methodological approach consists in starting from theories of human and animal development elaborated in fields such as developmental psychology, neuroscience, developmental and evolutionary biology, and linguistics, then to formalize and implement them in robots, sometimes exploring extensions or variants of them. The experimentation of those models in robots allows researchers to confront them with reality, and as a consequence, developmental robotics also provides feedback and novel hypotheses on theories of human and animal development.
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.
A cognitive architecture refers to both a theory about the structure of the human mind and to a computational instantiation of such a theory used in the fields of artificial intelligence (AI) and computational cognitive science. These formalized models can be used to further refine comprehensive theories of cognition and serve as the frameworks for useful artificial intelligence programs. Successful cognitive architectures include ACT-R and SOAR. The research on cognitive architectures as software instantiation of cognitive theories was initiated by Allen Newell in 1990.
A neural network, also called a neuronal network, is an interconnected population of neurons. Biological neural networks are studied to understand the organization and functioning of nervous systems.
Stephen Grossberg is a cognitive scientist, theoretical and computational psychologist, neuroscientist, mathematician, biomedical engineer, and neuromorphic technologist. He is the Wang Professor of Cognitive and Neural Systems and a Professor Emeritus of Mathematics & Statistics, Psychological & Brain Sciences, and Biomedical Engineering at Boston University.
Neuroinformatics is the emergent field that combines informatics and neuroscience. Neuroinformatics is related with neuroscience data and information processing by artificial neural networks. There are three main directions where neuroinformatics has to be applied:
Biocybernetics is the application of cybernetics to biological science disciplines such as neurology and multicellular systems. Biocybernetics plays a major role in systems biology, seeking to integrate different levels of information to understand how biological systems function. The field of cybernetics itself has origins in biological disciplines such as neurophysiology. Biocybernetics is an abstract science and is a fundamental part of theoretical biology, based upon the principles of systemics. Biocybernetics is a psychological study that aims to understand how the human body functions as a biological system and performs complex mental functions like thought processing, motion, and maintaining homeostasis.(PsychologyDictionary.org)Within this field, many distinct qualities allow for different distinctions within the cybernetic groups such as humans and insects such as beehives and ants. Humans work together but they also have individual thoughts that allow them to act on their own, while worker bees follow the commands of the queen bee. . Although humans often work together, they can also separate from the group and think for themselves.(Gackenbach, J. 2007) A unique example of this within the human sector of biocybernetics would be in society during the colonization period, when Great Britain established their colonies in North America and Australia. Many of the traits and qualities of the mother country were inherited by the colonies, as well as niche qualities that were unique to them based on their areas like language and personality—similar vines and grasses, where the parent plant produces offshoots, spreading from the core. Once the shoots grow their roots and get separated from the mother plant, they will survive independently and be considered their plant. Society is more closely related to plants than to animals since, like plants, there is no distinct separation between parent and offspring. The branching of society is more similar to plant reproduction than to animal reproduction. Humans are a k- selected species that typically have fewer offspring that they nurture for longer periods than r -selected species. It could be argued that when Britain created colonies in regions like North America and Australia, these colonies, once they became independent, should be seen as offspring of British society. Like all children, the colonies inherited many characteristics, such as language, customs and technologies, from their parents, but still developed their own personality. This form of reproduction is most similar to the type of vegetative reproduction used by many plants, such as vines and grasses, where the parent plant produces offshoots, spreading ever further from the core. When such a shoot, once it has produced its own roots, gets separated from the mother plant, it will survive independently and define a new plant. Thus, the growth of society is more like that of plants than like that of the higher animals that we are most familiar with, there is not a clear distinction between a parent and its offspring. Superorganisms are also capable of the so-called "distributed intelligence," a system composed of individual agents with limited intelligence and information. These can pool resources to complete goals beyond the individuals' reach on their own. Similar to the concept of "Game theory." In this concept, individuals and organisms make choices based on the behaviors of the other player to deem the most profitable outcome for them as an individual rather than a group.
Andrew Gordon Speedie Pask was a British cybernetician, inventor and polymath who made multiple contributions to cybernetics, educational psychology, educational technology, applied episteomology, chemical computing, architecture, and systems art. During his life, he gained three doctorate degrees. He was an avid writer, with more than two hundred and fifty publications which included a variety of journal articles, books, periodicals, patents, and technical reports. He worked as an academic and researcher for a variety of educational settings, research institutes, and private stakeholders including but not limited to the University of Illinois, Concordia University, the Open University, Brunel University and the Architectural Association School of Architecture. He is known for the development of conversation theory.
For holographic data storage, holographic associative memory (HAM) is an information storage and retrieval system based on the principles of holography. Holograms are made by using two beams of light, called a "reference beam" and an "object beam". They produce a pattern on the film that contains them both. Afterwards, by reproducing the reference beam, the hologram recreates a visual image of the original object. In theory, one could use the object beam to do the same thing: reproduce the original reference beam. In HAM, the pieces of information act like the two beams. Each can be used to retrieve the other from the pattern. It can be thought of as an artificial neural network which mimics the way the brain uses information. The information is presented in abstract form by a complex vector which may be expressed directly by a waveform possessing frequency and magnitude. This waveform is analogous to electrochemical impulses believed to transmit information between biological neuron cells.
The following outline is provided as an overview of and topical guide to automation:
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.
Cybernetics is the transdisciplinary study of circular processes such as feedback systems where outputs are also inputs. It is concerned with general principles that are relevant across multiple contexts, including in ecological, technological, biological, cognitive and social systems and also in practical activities such as designing, learning, and managing.
The IEEE Systems, Man, and Cybernetics Society is a professional society of the IEEE. It aims "to serve the interests of its members and the community at large by promoting the theory, practice, and interdisciplinary aspects of systems science and engineering, human-machine systems, and cybernetics".
Computational heuristic intelligence (CHI) refers to specialized programming techniques in computational intelligence. These techniques have the express goal of avoiding complexity issues, also called NP-hard problems, by using human-like techniques. They are best summarized as the use of exemplar-based methods (heuristics), rather than rule-based methods (algorithms). Hence the term is distinct from the more conventional computational algorithmic intelligence, or symbolic AI. An example of a CHI technique is the encoding specificity principle of Tulving and Thompson. In general, CHI principles are problem solving techniques used by people, rather than programmed into machines. It is by drawing attention to this key distinction that the use of this term is justified in a field already replete with confusing neologisms. Note that the legal systems of all modern human societies employ both heuristics from individual trial records as well as legislated statutes (rules) as regulatory guides.
This glossary of artificial intelligence is a list of definitions of terms and concepts relevant to the study of artificial intelligence, its sub-disciplines, and related fields. Related glossaries include Glossary of computer science, Glossary of robotics, and Glossary of machine vision.
Silvia Ferrari is an Italian-American aerospace engineer. She is John Brancaccio Professor at the Sibley School of Mechanical and Aerospace Engineering at Cornell University and also the director of the Laboratory for Intelligent Systems and Control (LISC) at the same university.
