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Computer science is the study of computation, automation, and information. Computer science spans theoretical disciplines to practical disciplines. Computer science is generally considered an academic discipline and distinct from computer programming which is considered to be a technical field.
Cognitive science is the interdisciplinary, scientific study of the mind and its processes with input from linguistics, psychology, neuroscience, philosophy, computer science/artificial intelligence, and anthropology. It examines the nature, the tasks, and the functions of cognition. Cognitive scientists study intelligence and behavior, with a focus on how nervous systems represent, process, and transform information. Mental faculties of concern to cognitive scientists include language, perception, memory, attention, reasoning, and emotion; to understand these faculties, cognitive scientists borrow from fields such as linguistics, psychology, artificial intelligence, philosophy, neuroscience, and anthropology. The typical analysis of cognitive science spans many levels of organization, from learning and decision to logic and planning; from neural circuitry to modular brain organization. One of the fundamental concepts of cognitive science is that "thinking can best be understood in terms of representational structures in the mind and computational procedures that operate on those structures."
The mind is the set of faculties responsible for all mental phenomena. Often the term is also identified with the phenomena themselves. These faculties include thought, imagination, memory, will, and sensation. They are responsible for various mental phenomena, like perception, pain experience, belief, desire, intention, and emotion. Various overlapping classifications of mental phenomena have been proposed. Important distinctions group them according to whether they are sensory, propositional, intentional, conscious, or occurrent. Minds were traditionally understood as substances but it is more common in the contemporary perspective to conceive them as properties or capacities possessed by humans and higher animals. Various competing definitions of the exact nature of the mind or mentality have been proposed. Epistemic definitions focus on the privileged epistemic access the subject has to these states. Consciousness-based approaches give primacy to the conscious mind and allow unconscious mental phenomena as part of the mind only to the extent that they stand in the right relation to the conscious mind. According to intentionality-based approaches, the power to refer to objects and to represent the world is the mark of the mental. For behaviorism, whether an entity has a mind only depends on how it behaves in response to external stimuli while functionalism defines mental states in terms of the causal roles they play. Central questions for the study of mind, like whether other entities besides humans have minds or how the relation between body and mind is to be conceived, are strongly influenced by the choice of one's definition.
Semantics is the study of reference, meaning, or truth. The term can be used to refer to subfields of several distinct disciplines, including philosophy, linguistics and computer science.
In their most common sense, the terms thought and thinking refer to conscious cognitive processes that can happen independently of sensory stimulation. Their most paradigmatic forms are judging, reasoning, concept formation, problem solving, and deliberation. But other mental processes, like considering an idea, memory, or imagination, are also often included. These processes can happen internally independent of the sensory organs, unlike perception. But when understood in the widest sense, any mental event may be understood as a form of thinking, including perception and unconscious mental processes. In a slightly different sense, the term thought refers not to the mental processes themselves but to mental states or systems of ideas brought about by these processes.
Scientific evidence is evidence that serves to either support or counter a scientific theory or hypothesis, although scientists also use evidence in other ways, such as when applying theories to practical problems. Such evidence is expected to be empirical evidence and interpretable in accordance with scientific methods. Standards for scientific evidence vary according to the field of inquiry, but the strength of scientific evidence is generally based on the results of statistical analysis and the strength of scientific controls.
Understanding is a psychological process related to an abstract or physical object, such as a person, situation, or message whereby one is able to use concepts to model that object. Understanding is a relation between the knower and an object of understanding. Understanding implies abilities and dispositions with respect to an object of knowledge that are sufficient to support intelligent behavior.
DNA computing is an emerging branch of unconventional computing which uses DNA, biochemistry, and molecular biology hardware, instead of the traditional electronic computing. Research and development in this area concerns theory, experiments, and applications of DNA computing. Although the field originally started with the demonstration of a computing application by Len Adleman in 1994, it has now been expanded to several other avenues such as the development of storage technologies, nanoscale imaging modalities, synthetic controllers and reaction networks, etc.
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.
In its most common sense, methodology is the study of research methods. However, the term can also refer to the methods themselves or to the philosophical discussion of associated background assumptions. A method is a structured procedure for bringing about a certain goal. In the context of research, this goal is usually to discover new knowledge or to verify pre-existing knowledge claims. This normally involves various steps, like choosing a sample, collecting data from this sample, and interpreting this data. The study of methods involves a detailed description and analysis of these processes. It includes evaluative aspects by comparing different methods to assess their advantages and disadvantages relative to different research goals and situations. This way, a methodology can help make the research process efficient and reliable by guiding researchers on which method to employ at each step. These descriptions and evaluations of methods often depend on philosophical background assumptions. The assumptions are about issues like how the studied phenomena are to be conceptualized, what constitutes evidence for or against them, and what the general goal of research is. When understood in the widest sense, methodology also includes the discussion of these more abstract issues.
The cognitive revolution was an intellectual movement that began in the 1950s as an interdisciplinary study of the mind and its processes. It later became known collectively as cognitive science. The relevant areas of interchange were between the fields of psychology, linguistics, computer science, anthropology, neuroscience, and philosophy. The approaches used were developed within the then-nascent fields of artificial intelligence, computer science, and neuroscience. In the 1960s, the Harvard Center for Cognitive Studies and the Center for Human Information Processing at the University of California, San Diego were influential in developing the academic study of cognitive science. By the early 1970s, the cognitive movement had surpassed behaviorism as a psychological paradigm. Furthermore, by the early 1980s the cognitive approach had become the dominant line of research inquiry across most branches in the field of psychology.
Scientific modelling is a scientific activity, the aim of which is to make a particular part or feature of the world easier to understand, define, quantify, visualize, or simulate by referencing it to existing and usually commonly accepted knowledge. It requires selecting and identifying relevant aspects of a situation in the real world and then developing a model to replicate a system with those features. Different types of models may be used for different purposes, such as conceptual models to better understand, operational models to operationalize, mathematical models to quantify, computational models to simulate, and graphical models to visualize the subject.
The history of computer science began long before the modern discipline of computer science, usually appearing in forms like mathematics or physics. Developments in previous centuries alluded to the discipline that we now know as computer science. This progression, from mechanical inventions and mathematical theories towards modern computer concepts and machines, led to the development of a major academic field, massive technological advancement across the Western world, and the basis of a massive worldwide trade and culture.
Digital humanities (DH) is an area of scholarly activity at the intersection of computing or digital technologies and the disciplines of the humanities. It includes the systematic use of digital resources in the humanities, as well as the analysis of their application. DH can be defined as new ways of doing scholarship that involve collaborative, transdisciplinary, and computationally engaged research, teaching, and publishing. It brings digital tools and methods to the study of the humanities with the recognition that the printed word is no longer the main medium for knowledge production and distribution.
In philosophy of mind, the computational theory of mind (CTM), also known as computationalism, is a family of views that hold that the human mind is an information processing system and that cognition and consciousness together are a form of computation. Warren McCulloch and Walter Pitts (1943) were the first to suggest that neural activity is computational. They argued that neural computations explain cognition. The theory was proposed in its modern form by Hilary Putnam in 1967, and developed by his PhD student, philosopher, and cognitive scientist Jerry Fodor in the 1960s, 1970s, and 1980s. Despite being vigorously disputed in analytic philosophy in the 1990s due to work by Putnam himself, John Searle, and others, the view is common in modern cognitive psychology and is presumed by many theorists of evolutionary psychology. In the 2000s and 2010s the view has resurfaced in analytic philosophy.
Open data is data that is openly accessible, exploitable, editable and shared by anyone for any purpose. Open data is licensed under an open license.
Gualtiero Piccinini is an Italian–American philosopher known for his work on the nature of mind and computation as well as on how to integrate psychology and neuroscience. He is Curators' Distinguished Professor in the Philosophy Department and Associate Director of the Center for Neurodynamics at the University of Missouri, St. Louis.
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.
Digital archaeology is the application of information technology and digital media to archaeology. It includes the use of digital photography, 3D reconstruction, virtual reality, and geographical information systems, among other techniques. Computational archaeology, which covers computer-based analytical methods, can be considered a subfield of digital archaeology, as can virtual archaeology.
Patrick Grim is an American philosopher. He has published on epistemic questions in philosophy of religion, as well as topics in philosophy of science, philosophy of logic, computational philosophy, and agent-based modeling. He is author, co-author or editor of seven books in philosophical logic, philosophy of mind, philosophy of science and computational philosophy. He is currently editor of the American Philosophical Quarterly and founding co-editor of over forty volumes of The Philosopher’s Annual, an attempt to collect the ten best philosophy articles of the year. Grim's popular work includes four video lecture series on value theory, informal logic, and philosophy of mind for The Great Courses. Grim's academic posts have included Distinguished Teaching Professor of Philosophy (Emeritus) at the State University of New York at Stony Brook, Distinguished Visiting Professor in Philosophy at the University of Michigan at Ann Arbor, and fellowships and lectureships at the Center for Complex Systems at the University of Michigan at Ann Arbor and at the Center for Philosophy of Science at the University of Pittsburgh.
References
- ↑ Allen, Colin; Beavers, Tony (September 2011). "Synthese special issue: representing philosophy". Synthese . 182 (2): 181–183. doi: 10.1007/s11229-009-9664-z . ISSN 0039-7857. S2CID 28405175.
- ↑ Pence, Charles H.; Ramsey, Grant (December 2018). "How to Do Digital Philosophy of Science". Philosophy of Science . 85 (5): 930–941. doi:10.1086/699697. ISSN 0031-8248. S2CID 65311603.
- Grim, Patrick; Singer, Daniel (Spring 2020). "Computational Philosophy". In Zalta, Edward N. (ed.). Stanford Encyclopedia of Philosophy .
- Grim, Patrick (13 December 2019). "Editorial introduction to the Topical Issue 'Computer Modeling in Philosophy'". Open Philosophy. 2 (1): 653–656. doi: 10.1515/opphil-2019-0049 .
