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Anticipation (artificial Intelligence)
In artificial intelligence (AI), anticipation occurs when an Intelligent agent, 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 t ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Artificial Intelligence
Artificial intelligence (AI) is the capability of computer, computational systems to perform tasks typically associated with human intelligence, such as learning, reasoning, problem-solving, perception, and decision-making. It is a field of research in computer science that develops and studies methods and software that enable machines to machine perception, perceive their environment and use machine learning, learning and intelligence to take actions that maximize their chances of achieving defined goals. High-profile applications of AI include advanced web search engines (e.g., Google Search); recommendation systems (used by YouTube, Amazon (company), Amazon, and Netflix); virtual assistants (e.g., Google Assistant, Siri, and Amazon Alexa, Alexa); autonomous vehicles (e.g., Waymo); Generative artificial intelligence, generative and Computational creativity, creative tools (e.g., ChatGPT and AI art); and Superintelligence, superhuman play and analysis in strategy games (e.g., ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Intelligent Agent
In artificial intelligence, an intelligent agent is an entity that Machine perception, perceives its environment, takes actions autonomously to achieve goals, and may improve its performance through machine learning or by acquiring knowledge representation, knowledge. Leading AI textbooks define artificial intelligence as the "study and design of intelligent agents," emphasizing that goal-directed behavior is central to intelligence. A specialized subset of intelligent agents, agentic AI (also known as an AI agent or simply agent), expands this concept by proactively pursuing goals, making decisions, and taking actions over extended periods, thereby exemplifying a novel form of digital agency. Intelligent agents can range from simple to highly complex. A basic thermostat or control system is considered an intelligent agent, as is a human being, or any other system that meets the same criteria—such as a firm, a state (polity), state, or a biome. Intelligent agents operate ba ... [...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 study in artificial intelligence concerned with the development and study of Computational statistics, statistical algorithms that can learn from data and generalise to unseen data, and thus perform Task (computing), tasks without explicit Machine code, instructions. Within a subdiscipline in machine learning, advances in the field of deep learning have allowed Neural network (machine learning), neural networks, a class of statistical algorithms, to surpass many previous machine learning approaches in performance. ML finds application in many fields, including natural language processing, computer vision, speech recognition, email filtering, agriculture, and medicine. The application of ML to business problems is known as predictive analytics. Statistics and mathematical optimisation (mathematical programming) methods comprise the foundations of machine learning. Data mining is a related field of study, focusing on exploratory data analysi ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Automated Planning And Scheduling
Automated planning and scheduling, sometimes denoted as simply AI planning, is a branch of artificial intelligence that concerns the realization of strategies or action sequences, typically for execution by intelligent agents, autonomous robots and unmanned vehicles. Unlike classical control and classification problems, the solutions are complex and must be discovered and optimized in multidimensional space. Planning is also related to decision theory. In known environments with available models, planning can be done offline. Solutions can be found and evaluated prior to execution. In dynamically unknown environments, the strategy often needs to be revised online. Models and policies must be adapted. Solutions usually resort to iterative trial and error processes commonly seen in artificial intelligence. These include dynamic programming, reinforcement learning and combinatorial optimization. Languages used to describe planning and scheduling are often called action language ... [...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 behavior 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 ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Cognition
Cognition is 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, imagination, 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. Cognitive processes use existing knowledge to discover new knowledge. Cognitive processes are analyzed from very 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) are synthesized in the developing field of cognitive science, a progressively autonomou ... [...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 Brazil. 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 Asi] c ... [...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 study of logic and formal reasoning from antiquity to the present led directly to the invention of the programmable digital computer in the 1940s, a machine based on abstract mathematical reasoning. This device and the ideas behind it inspired scientists to begin 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 in 1956. Attendees of the workshop became the leaders of AI research for decades. Many of them predicted that machines as intelligent as humans would exist within a generation. The U.S. government provided millions of dollars with the hope of making this vision come true. Eventually, it became obvious that researchers had grossly underestimated the difficulty of this feat. In 1974, ... [...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 relative influence on human beings of their genetic inheritance (nature) and the environmental conditions of their development ( 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 (). 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 ''On the Origin of Sp ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
