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CH08_withFigures
CH08_withFigures

... interconnectivity—each neuron is connected to every other neuron – The output of each neuron may depend on its previous values – One use of Hopfield networks: Solving constrained optimization problems, such as the classic traveling salesman problem (TSP) ...
From: AAAI Technical Report S-0 -0 . Compilation copyright © 200
From: AAAI Technical Report S-0 -0 . Compilation copyright © 200

... Hans W. Guesgen Composition for Cardinal Directions by Decomposing Horizontal and Vertical Constraints / 39 Ah Lian Kor and Brandon Bennett Spatial and Temporal Reasoning: Beyond Allen's Calculus / 46 Gérard Ligozat, Debasis Mitra, and Jean-François Condotta STCSP: A Representation Model for Sequent ...
Machine Learning for Medical Diagnosis
Machine Learning for Medical Diagnosis

... to organize large files of records to reveal complex interactions in a manner that can be understood by the human investigator. Some help can be obtained by using computer oriented techniques of information retrieval, such as program to print selected two- and three-way tables plotting one variable ...
Principles of Rule-Based Expert Systems
Principles of Rule-Based Expert Systems

... or transparency, nor does it guarantee high performance. But if a packaged framework of inferences and control procedures can be used, the design of a new system properly focuses on the expertise needed for high performance. For many years, AI research has focused on heuristic reasoning. Heuristics, ...
AI PLANNING FOR TRANSPORTATION LOGISTICS
AI PLANNING FOR TRANSPORTATION LOGISTICS

... The recent evolution of the domain independent heuristic planning started with the work of Drew McDermott ([13], [14]) and the UNPOP planner. The planner is not restricted to pure STRIPS representations, supporting the more expressive ADL language [16]. UNPOP proceeds forwards in the state-space. Es ...
INTELLIGENT AGENT PLANNING WITH QUASI
INTELLIGENT AGENT PLANNING WITH QUASI

... SARSA [16] need to discretize the continuous input states of the problem. The Q function, used to determine the best action to be taken in a particular state, is defined as Q : S × A → ℜ and is usually implemented as a matrix containing the real-valued rewards r ∈ ℜ given by the environment in a par ...
AAAI-08 will again include the Nectar Although papers will describe previously
AAAI-08 will again include the Nectar Although papers will describe previously

... AAAI-08 will again include the Nectar track (new scientific and technical advances in research). This track aims to make the most significant AI results presented at other conferences in the last two years available to a broad AI audience. One important goal of the track is to offer researchers the ...
Ordered Task Decomposition 1 - Information Sciences Institute
Ordered Task Decomposition 1 - Information Sciences Institute

... Quinn), we have embedded SHOP as the automated planning module in the HICAP system for NEO plan authoring [Munoz-Avila et al., 1999a; Munoz-Avila et al., 1999b]. HICAP dynamically elaborates plans, derived from military doctrine on NEOs and represented as HTNs (hierarchical task networks), via inter ...
Principles of Information Systems, Ninth Edition
Principles of Information Systems, Ninth Edition

... • Knowledge management allows organizations to share knowledge and experience among their managers and employees – Discuss the differences among data, information, and knowledge – Describe the role of the chief knowledge officer (CKO) – List some of the tools and techniques used in knowledge managem ...
Chapter 2 Intelligent Agents
Chapter 2 Intelligent Agents

Knowledge Management Systems: Development and Applications Part II: Techniques and Examples
Knowledge Management Systems: Development and Applications Part II: Techniques and Examples

... Linguistic analysis/NLP: identify key concepts (who/what/where…) Statistical/co-occurrence analysis: create automatic thesaurus, link analysis Statistical and neural networks clustering/categorization: identify similar documents/users/communities and create knowledge maps Visualization and HCI: tree ...
decisions making in design process – examples of artificial
decisions making in design process – examples of artificial

... number of gear power transmitters shifting and gear ratios is done based on the recommendations for minimal mass and volume of power gear transmitter. These recommendations are for helical, cone and helicalcone one, two or three step power gear transmitters. All of these recommendations are used in ...
Chapter 11
Chapter 11

... Artificial Intelligence in Perspective • Artificial intelligence systems: people, procedures, hardware, software, data, and knowledge needed to develop computer systems and machines that demonstrate characteristics of intelligence • Researchers, scientists, and experts on how human beings think are ...
Artificial Intelligence Comes of Age
Artificial Intelligence Comes of Age

... daughter of Lord Byron — wrote a seminal scientific article about the nature of computing. As Isaacson wrote, “It raised what is still the most fascinating metaphysical topic involving computers, that of artificial intelligence. Can machines think?” Lovelace emphatically rejected this proposition wi ...
kb1
kb1

... • A knowledge-based agent needs a knowledge base and an inference mechanism. It operates by storing sentences in its knowledge base, inferring new sentences with the inference mechanism, and using them to deduce which actions to take. • The interpretation of a sentence is the fact to which it refers ...
THE CHALLENGE OF INTELLIGENT SYSTEMS
THE CHALLENGE OF INTELLIGENT SYSTEMS

... We must declare the domain of application for which we need the intelligent controller. A distinction is made between closed and open systems. Closed systems can be characterized by clear assignments of the problem to be solved and the ability to construct a complete list of concrete user specificat ...
Lindenmayer Systems (L-systems)
Lindenmayer Systems (L-systems)

... Central Question in Morphogenesis: How the information coded in linear DNA molecules becomes translated into a three-dimensional form? Going from Genotype to Phenotype General assumption: the DNA does not specify 'as some kind of description' or ‘blueprint’ the final form of the body. More like 'a r ...
Evolutionary Computing
Evolutionary Computing

... Does not say that comparisons between algorithms are useless. Does not say that there does not exist a subset of problems that are more relevant than the set of all problems. ...
IX - AIAI - The University of Edinburgh
IX - AIAI - The University of Edinburgh

... extreme can be a user-driven approach followed by system agents “filling-in” the details, or the opposite extreme of a fully automatic system-driven approach (with perhaps occasional appeals to a user to take predefined decisions). In more practical use, we envisage a mixed-initiative form of intera ...
The computing legacy of Alan M. Turing
The computing legacy of Alan M. Turing

... symbol on the tape may therefore eventually have an innings1.’ The graphical diagram denotes a typical TM with the finite state control along with the tape and tape head. In other words, the operations that this machine can perform be described as follows: Based on the state of the finite state cont ...
Artificial intelligence - National Open University of Nigeria
Artificial intelligence - National Open University of Nigeria

Building Intelligent Tutoring Systems: An Overview
Building Intelligent Tutoring Systems: An Overview

... (Ikeda and Mizoguchi 1994) is a good example of such a shell. FITS is a domainindependent framework that provides building blocks for student, tutor and domain modeling. Recently, Stankov et al. (2008) developed a system called the Tutor–Expert System (Tex-Sys). Tex-Sys is an ITS shell that provides ...
International Journal of Multidisciplinary Approach and Studies
International Journal of Multidisciplinary Approach and Studies

... 72 important nerves in the body. Raga lakshana (norms) and sruti shuddhi, (pitch purity) the raga could affect the particular nerve in the body in a favorable manner [32, 33]. The listening time called Prahar is also important of the Raga. It is become more effective if that Raga is listen at that R ...
What does the Turing test really mean? And how many human beings
What does the Turing test really mean? And how many human beings

... man-machine distinction. Yet raising a human child should hardly count as an advance in computer science or artificial intelligence. Turing jokes that perhaps the team of engineers will have to be all of one sex (another implicit reference to homosexuality), so as to rule out biologically conceived ...
pdf
pdf

... This example shows different elements. The first part of the process is described in terms of (Sun, 2000, 2002)’s subconceptual level, whereas the last part of the process is viewed in terms of the conceptual level. For both parts of the process the notion of representational content has been discus ...
< 1 ... 65 66 67 68 69 70 71 72 73 ... 241 >

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; as Pamela McCorduck writes, AI began with ""an ancient wish to forge the gods.""The seeds of modern AI were planted by classical 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 conference on the campus of Dartmouth College in 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 this vision come true. Eventually it became obvious that they had grossly underestimated the difficulty of the project. In 1973, in response to the criticism of James Lighthill and ongoing pressure from congress, the U.S. and British Governments stopped funding undirected research into artificial intelligence. Seven years later, a visionary initiative by the Japanese Government inspired governments and industry to provide AI with billions of dollars, but by the late 80s the investors became disillusioned and withdrew funding again. This cycle of boom and bust, of ""AI winters"" and summers, continues to haunt the field. Undaunted, there are those who make extraordinary predictions even now.Progress in AI has continued, despite the rise and fall of its reputation in the eyes of government bureaucrats and venture capitalists. Problems that had begun to seem impossible in 1970 have been solved and the solutions are now used in successful commercial products. However, no machine has been built with a human level of intelligence, contrary to the optimistic predictions of the first generation of AI researchers. ""We can only see a short distance ahead,"" admitted Alan Turing, in a famous 1950 paper that catalyzed the modern search for machines that think. ""But,"" he added, ""we can see much that must be done.""
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