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Anticipation (artificial Intelligence)
In artificial intelligence (AI), anticipation occurs when an agent makes decisions based on its explicit beliefs about the future. More broadly, "anticipation" can also refer to the ability to act in appropriate ways that take future events into account, without necessarily explicitly possessing a model of the future events. The concept stays in contrast to the reactive paradigm, which is not able to predict future system states.{{cite book, author1=Giovanni Pezzulo, author2=Martin V. Butz, author3=Cristiano Castelfranchi, title=The Challenge of Anticipation: A Unifying Framework for the Analysis and Design of Artificial Cognitive Systems, url=https://books.google.com/books?id=v3NqCQAAQBAJ&pg=PA6, date=25 September 2008, publisher=Springer, isbn=978-3-540-87702-8, pages=6 In AI An agent employing anticipation would try to predict the future state of the environment (weather in this case) and make use of the predictions in the decision making. For example, If the sky is cloudy an ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Artificial Intelligence
Artificial intelligence (AI) is intelligence—perceiving, synthesizing, and inferring information—demonstrated by machines, as opposed to intelligence displayed by animals and humans. Example tasks in which this is done include speech recognition, computer vision, translation between (natural) languages, as well as other mappings of inputs. The ''Oxford English Dictionary'' of Oxford University Press defines artificial intelligence as: the theory and development of computer systems able to perform tasks that normally require human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages. AI applications include advanced web search engines (e.g., Google), recommendation systems (used by YouTube, Amazon and Netflix), understanding human speech (such as Siri and Alexa), self-driving cars (e.g., Tesla), automated decision-making and competing at the highest level in strategic game systems (such as chess and Go). ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Intelligent Agent
In artificial intelligence, an intelligent agent (IA) is anything which perceives its environment, takes actions autonomously in order to achieve goals, and may improve its performance with learning or may use knowledge. They may be simple or complex — a thermostat is considered an example of an intelligent agent, as is a human being, as is any system that meets the definition, such as a firm, a state, or a biome. Leading AI textbooks define "artificial intelligence" as the "study and design of intelligent agents", a definition that considers goal-directed behavior to be the essence of intelligence. Goal-directed agents are also described using a term borrowed from economics, "rational agent". An agent has an "objective function" that encapsulates all the IA's goals. Such an agent is designed to create and execute whatever plan will, upon completion, maximize the expected value of the objective function. For example, a reinforcement learning agent has a "reward function ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Robert Rosen (theoretical Biologist)
Robert Rosen (June 27, 1934 – December 28, 1998) was an American theoretical biologist and Professor of Biophysics at Dalhousie University. Career Rosen was born on June 27, 1934 in Brownsville (a section of Brooklyn), in New York City. He studied biology, mathematics, physics, philosophy, and history; particularly, the history of science. In 1959 he obtained a PhD in relational biology, a specialization within the broader field of Mathematical Biology, under the guidance of Professor Nicolas Rashevsky at the University of Chicago. He remained at the University of Chicago until 1964,"Autobiographical Reminiscences of Robert Rosen" later moving to the University of Buffalo — now part of the |
Machine Learning
Machine learning (ML) is a field of inquiry devoted to understanding and building methods that 'learn', that is, methods that leverage data to improve performance on some set of tasks. It is seen as a part of artificial intelligence. Machine learning algorithms build a model based on sample data, known as training data, in order to make predictions or decisions without being explicitly programmed to do so. Machine learning algorithms are used in a wide variety of applications, such as in medicine, email filtering, speech recognition, agriculture, and computer vision, where it is difficult or unfeasible to develop conventional algorithms to perform the needed tasks.Hu, J.; Niu, H.; Carrasco, J.; Lennox, B.; Arvin, F.,Voronoi-Based Multi-Robot Autonomous Exploration in Unknown Environments via Deep Reinforcement Learning IEEE Transactions on Vehicular Technology, 2020. A subset of machine learning is closely related to computational statistics, which focuses on making predicti ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Automated Planning And Scheduling
Automation describes a wide range of technologies that reduce human intervention in processes, namely by predetermining decision criteria, subprocess relationships, and related actions, as well as embodying those predeterminations in machines. Automation has been achieved by various means including Mechanical system, mechanical, hydraulic, pneumatic, electrical, electronic devices, and computers, usually in combination. Complicated systems, such as modern factories, airplanes, and ships typically use combinations of all of these techniques. The benefit of automation includes labor savings, reducing waste, savings in electricity costs, savings in material costs, and improvements to quality, accuracy, and precision. Automation includes the use of various equipment and control systems such as machinery, processes in factories, boilers, and heat-treating ovens, switching on telephone networks, steering, and stabilization of ships, aircraft, and other applications and vehicles with ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Action Selection
Action selection is a way of characterizing the most basic problem of intelligent systems: what to do next. In artificial intelligence and computational cognitive science, "the action selection problem" is typically associated with intelligent agents and animats—artificial systems that exhibit complex behaviour in an agent environment. The term is also sometimes used in ethology or animal behavior. One problem for understanding action selection is determining the level of abstraction used for specifying an "act". At the most basic level of abstraction, an atomic act could be anything from ''contracting a muscle cell'' to ''provoking a war''. Typically for any one action-selection mechanism, the set of possible actions is predefined and fixed. Most researchers working in this field place high demands on their agents: * The acting agent typically must select its action in dynamic and unpredictable environments. * The agents typically act in real time; therefore they must make de ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Cognition
Cognition refers to "the mental action or process of acquiring knowledge and understanding through thought, experience, and the senses". It encompasses all aspects of intellectual functions and processes such as: perception, attention, thought, intelligence, the formation of knowledge, memory and working memory, judgment and evaluation, reasoning and computation, problem solving and decision making, comprehension and production of language. Imagination is also a cognitive process, it is considered as such because it involves thinking about possibilities. Cognitive processes use existing knowledge and discover new knowledge. Cognitive processes are analyzed from different perspectives within different contexts, notably in the fields of linguistics, musicology, anesthesia, neuroscience, psychiatry, psychology, education, philosophy, anthropology, biology, systemics, logic, and computer science. These and other approaches to the analysis of cognition (such as embodied cognition) ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Dynamic Planning
is a licensing company owned by manga artist Go Nagai. It was established in 1974 as a sister company of Dynamic Productions. Dynamic Planning is credited in all of Go Nagai's animated works since 1974 as the "planner" and/or "producer". Since the '70s, Toei exported their anime collaborations with Dynamic Planning without their permission (Go Nagai was unaware of that fact) to Europe, Asia and America. Mazinger Z is extremely popular in Spain, Latin America and throughout Asia: UFO Robot Grendizer (aka Goldorak and Goldrake between 1976 and 1980 was a huge hit in Italy and France; Groizer X (aka O Pirata do Espaço ) was a '80s hit in Brasil. The popular Super Robot Wars's console game features most of Dynamic Planning's giant robot characters. In 1994 Dynamic Planning established an International Division, directed by Go Nagai's brother Kenji Nagai (永井謙次) and Federico Colpi, which soon established a network of associated companies throughout Europe and Asia calle ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
History Of Artificial Intelligence
The history of artificial intelligence (AI) began in antiquity, with myths, stories and rumors of artificial beings endowed with intelligence or consciousness by master craftsmen. The seeds of modern AI were planted by philosophers who attempted to describe the process of human thinking as the mechanical manipulation of symbols.This work culminated in the invention of the programmable digital computer in the 1940s, a machine based on the abstract essence of mathematical reasoning. This device and the ideas behind it inspired a handful of scientists to begin seriously discussing the possibility of building an electronic brain. The field of AI research was founded at a workshop held on the campus of Dartmouth College, USA during the summer of 1956. Those who attended would become the leaders of AI research for decades. Many of them predicted that a machine as intelligent as a human being would exist in no more than a generation, and they were given millions of dollars to make ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
MindRACES
The Framework Programmes for Research and Technological Development, also called Framework Programmes or abbreviated FP1 to FP9, are funding programmes created by the European Union/European Commission to support and foster research in the European Research Area (ERA). Starting in 2014, the funding programmes were named Horizon. The funding programmes began in 1984 and continue to the present day. The most recent programme, Horizon Europe, has a budget of 95.5 billion Euros to be distributed over 7 years. The specific objectives and actions vary between funding periods. In FP6 and FP7, focus was on technological research. In Horizon 2020, the focus was on innovation, delivering economic growth faster, and delivering solutions to end users that are often governmental agencies. Background Conducting European research policies and implementing European research programmes is an obligation under the Amsterdam Treaty, which includes a chapter on research and technological development. ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Nature And Nurture
Nature versus nurture is a long-standing debate in biology and society about the balance between two competing factors which determine fate: genetics (nature) and environment (nurture). The alliterative expression "nature and nurture" in English has been in use since at least the Elizabethan period and goes back to medieval French. The complementary combination of the two concepts is an ancient concept ( grc, ἁπό φύσεως καὶ εὐτροφίας). Nature is what people think of as pre-wiring and is influenced by genetic inheritance and other biological factors. Nurture is generally taken as the influence of external factors after conception e.g. the product of exposure, experience and learning on an individual. The phrase in its modern sense was popularized by the Victorian polymath Francis Galton, the modern founder of eugenics and behavioral genetics when he was discussing the influence of heredity and environment on social advancement. Galton was influenced by ''O ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
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