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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] |
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] |
Attention
Attention or focus, is the concentration of awareness on some phenomenon to the exclusion of other stimuli. It is the selective concentration on discrete information, either subjectively or objectively. William James (1890) wrote that "Attention is the taking possession by the mind, in clear and vivid form, of one out of what seem several simultaneously possible objects or trains of thought. Focalization, concentration, of consciousness are of its essence." Attention has also been described as the allocation of limited cognitive processing resources. Attention is manifested by an attentional bottleneck, in terms of the amount of data the brain can process each second; for example, in human vision, less than 1% of the visual input data stream of 1MByte/sec can enter the bottleneck, leading to inattentional blindness. Attention remains a crucial area of investigation within education, psychology, neuroscience, cognitive neuroscience, and neuropsychology. Areas of activ ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Physical Symbol System
A physical symbol system (also called a formal system) takes physical patterns (symbols), combining them into structures (expressions) and manipulating them (using processes) to produce new expressions. The physical symbol system hypothesis (PSSH) is a position in the philosophy of artificial intelligence formulated by Allen Newell and Herbert A. Simon. They wrote: This claim implies both that human thinking is a kind of symbol manipulation (because a symbol system is necessary for intelligence) and that machines can be intelligent (because a symbol system is sufficient for intelligence). The idea has philosophical roots in Thomas Hobbes (who claimed reasoning was "nothing more than reckoning"), Gottfried Wilhelm Leibniz (who attempted to create a logical calculus of all human ideas), David Hume (who thought perception could be reduced to "atomic impressions") and even Immanuel Kant (who analyzed all experience as controlled by formal rules)., The latest version is called the ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Logical Argument
An argument is a series of Sentence (linguistics), sentences, Statement (logic), statements, or propositions some of which are called premises and one is the Logical consequence, conclusion. The purpose of an argument is to give Reason (argument), reasons for one's conclusion via justification, explanation, and/or persuasion. Arguments are intended to determine or show the degree of truth or acceptability of another statement called a conclusion. The process of crafting or delivering arguments, argumentation, can be studied from three main perspectives: the logical, the dialectical and the rhetorical perspective. In logic, an argument is usually expressed not in natural language but in a symbolic formal language, and it can be defined as any group of propositions of which one is claimed to follow from the others through Deductive reasoning, deductively valid inferences that preserve truth from the premises to the conclusion. This logical perspective on argument is relevant for sc ... [...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] |
Scientific Model
Scientific modelling is an activity that produces models representing empirical objects, phenomena, and physical processes, to make a particular part or feature of the world easier to understand, define, quantify, visualize, or simulate. 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. Modelling is an essential and inseparable part of many scientific disciplines, each of which has its own ideas about specific types of modelling. The following was said by John von Neumann. There is also an increasing attention to scientific modelling in fields such as science education, philosophy of science, systems theory ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Reactive Planning
{{nofootnotes, date=February 2011 In artificial intelligence, reactive planning denotes a group of techniques for action selection by autonomous agents. These techniques differ from classical planning in two aspects. First, they operate in a timely fashion and hence can cope with highly dynamic and unpredictable environments. Second, they compute just one next action in every instant, based on the current context. Reactive planners often (but not always) exploit reactive plans, which are stored structures describing the agent's priorities and behaviour. The term ''reactive planning'' goes back to at least 1988, and is synonymous with the more modern term dynamic planning. Reactive plan representation There are several ways to represent a reactive plan. All require a basic representational unit and a means to compose these units into plans. Condition-action rules (productions) A condition action rule, or if-then rule, is a rule in the form: if ''condition'' then ''action ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Distributed Systems
Distributed computing is a field of computer science that studies distributed systems, defined as computer systems whose inter-communicating components are located on different computer network, networked computers. The components of a distributed system communicate and coordinate their actions by message passing, passing messages to one another in order to achieve a common goal. Three significant challenges of distributed systems are: maintaining Concurrency (computer science), concurrency of components, overcoming the clock synchronization, lack of a global clock, and managing the independent failure of components. When a component of one system fails, the entire system does not fail. Examples of distributed systems vary from service-oriented architecture, SOA-based systems to microservices to massively multiplayer online games to peer-to-peer, peer-to-peer applications. Distributed systems cost significantly more than monolithic architectures, primarily due to increased needs ... [...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] |
Agent Architecture
Agent architecture in computer science is a blueprint for software agents and intelligent control systems, depicting the arrangement of components. The architectures implemented by intelligent agents are referred to as cognitive architectures. The term agent is a conceptual idea, but not defined precisely. It consists of facts, set of goals and sometimes a plan library. Types Reactive architectures *Deliberative reasoning architectures *[...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Tractable Problem
In theoretical computer science and mathematics, computational complexity theory focuses on classifying computational problems according to their resource usage, and explores the relationships between these classifications. A computational problem is a task solved by a computer. A computation problem is solvable by mechanical application of mathematical steps, such as an algorithm. A problem is regarded as inherently difficult if its solution requires significant resources, whatever the algorithm used. The theory formalizes this intuition, by introducing mathematical models of computation to study these problems and quantifying their computational complexity, i.e., the amount of resources needed to solve them, such as time and storage. Other measures of complexity are also used, such as the amount of communication (used in communication complexity), the number of gates in a circuit (used in circuit complexity) and the number of processors (used in parallel computing). One of the ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
Combinatorics
Combinatorics is an area of mathematics primarily concerned with counting, both as a means and as an end to obtaining results, and certain properties of finite structures. It is closely related to many other areas of mathematics and has many applications ranging from logic to statistical physics and from evolutionary biology to computer science. Combinatorics is well known for the breadth of the problems it tackles. Combinatorial problems arise in many areas of pure mathematics, notably in algebra, probability theory, topology, and geometry, as well as in its many application areas. Many combinatorial questions have historically been considered in isolation, giving an ''ad hoc'' solution to a problem arising in some mathematical context. In the later twentieth century, however, powerful and general theoretical methods were developed, making combinatorics into an independent branch of mathematics in its own right. One of the oldest and most accessible parts of combinatorics ... [...More Info...] [...Related Items...] OR: [Wikipedia] [Google] [Baidu] |
