Proceedings of the Twelfth National Conference on Artificial Intelligence PDF Download
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Author: American Association for Artificial Intelligence
Publisher:
ISBN:
Category : Artificial intelligence
Languages : en
Pages : 868
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Book Description
Author: American Association for Artificial Intelligence
Publisher:
ISBN:
Category : Artificial intelligence
Languages : en
Pages : 868
Get Book Here
Book Description
Author: Cognitive Science Society (U.S.). Conference
Publisher: Psychology Press
ISBN: 9780805809381
Category : Psychology
Languages : en
Pages : 554
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Book Description
First published in 1990. Routledge is an imprint of Taylor & Francis, an informa company.
Author: Ian Gent
Publisher:
ISBN: 9784274903632
Category : Computer algorithms
Languages : en
Pages : 568
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Book Description
Author: Nils J. Nilsson
Publisher: Morgan Kaufmann
ISBN: 1558604677
Category : Computers
Languages : en
Pages : 537
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Book Description
Nilsson employs increasingly capable intelligent agents in an evolutionary approach--a novel perspective from which to view and teach topics in artificial intelligence.
Author:
Publisher: IOS Press
ISBN:
Category :
Languages : en
Pages : 4947
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Book Description
Author: Alexander Nareyek
Publisher: Springer Science & Business Media
ISBN: 3540428984
Category : Business & Economics
Languages : en
Pages : 179
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Book Description
This book constitutes the thoroughly refereed post-proceedings of the International Workshop on Local Search for Planning and Scheduling, held at a satellite workshop of ECAI 2000 in Berlin, Germany in August 2000. The nine revised full papers presented together with an invited survey on meta-heuristics have gone through two rounds of reviewing and improvement. The papers are organized in topical sections on combinatorial optimization, planning with resources, and related approaches.
Author: Maximos A. Kaliakatsos-Papakostas
Publisher: Elsevier Inc. Chapters
ISBN: 0128068965
Category : Computers
Languages : en
Pages : 21
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Book Description
Automatic music composition has blossomed with the introduction of intelligent methodologies in computer science. Thereby, many methodologies for automatic music composition have been or could be described as “intelligent,” but what exactly is it that makes them intelligent? Furthermore, is there any categorization of intelligent music composition (IMC) methodologies that is both consistent and descriptive? This chapter aims to provide some insights on what IMC methodologies are, through proposing and analyzing a detailed categorization of them. Toward this perspective, methodologies that incorporate bioinspired intelligent algorithms (such as cellular automata, L-systems, genetic algorithms, swarm intelligence, among others) as well as their combinations are considered and briefly reviewed. At the same time, a consistent categorization of these methodologies is proposed, taking into account the utilization of their intelligent algorithm in accordance to their overall compositional aims. To this end, three main categories can be defined: the “unsupervised,” the “supervised,” and the “interactive” IMC methodologies.
Author: Xin-She Yang
Publisher: Newnes
ISBN: 0124051774
Category : Computers
Languages : en
Pages : 445
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Book Description
Swarm Intelligence and bio-inspired computation have become increasing popular in the last two decades. Bio-inspired algorithms such as ant colony algorithms, bat algorithms, bee algorithms, firefly algorithms, cuckoo search and particle swarm optimization have been applied in almost every area of science and engineering with a dramatic increase of number of relevant publications. This book reviews the latest developments in swarm intelligence and bio-inspired computation from both the theory and application side, providing a complete resource that analyzes and discusses the latest and future trends in research directions. It can help new researchers to carry out timely research and inspire readers to develop new algorithms. With its impressive breadth and depth, this book will be useful for advanced undergraduate students, PhD students and lecturers in computer science, engineering and science as well as researchers and engineers. - Focuses on the introduction and analysis of key algorithms - Includes case studies for real-world applications - Contains a balance of theory and applications, so readers who are interested in either algorithm or applications will all benefit from this timely book.
Author: John E. Laird
Publisher: MIT Press
ISBN: 0262538539
Category : Computers
Languages : en
Pages : 391
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Book Description
The definitive presentation of Soar, one AI's most enduring architectures, offering comprehensive descriptions of fundamental aspects and new components. In development for thirty years, Soar is a general cognitive architecture that integrates knowledge-intensive reasoning, reactive execution, hierarchical reasoning, planning, and learning from experience, with the goal of creating a general computational system that has the same cognitive abilities as humans. In contrast, most AI systems are designed to solve only one type of problem, such as playing chess, searching the Internet, or scheduling aircraft departures. Soar is both a software system for agent development and a theory of what computational structures are necessary to support human-level agents. Over the years, both software system and theory have evolved. This book offers the definitive presentation of Soar from theoretical and practical perspectives, providing comprehensive descriptions of fundamental aspects and new components. The current version of Soar features major extensions, adding reinforcement learning, semantic memory, episodic memory, mental imagery, and an appraisal-based model of emotion. This book describes details of Soar's component memories and processes and offers demonstrations of individual components, components working in combination, and real-world applications. Beyond these functional considerations, the book also proposes requirements for general cognitive architectures and explicitly evaluates how well Soar meets those requirements.
Author: David W. Aha
Publisher: Springer Science & Business Media
ISBN: 9401720533
Category : Computers
Languages : en
Pages : 421
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Book Description
This edited collection describes recent progress on lazy learning, a branch of machine learning concerning algorithms that defer the processing of their inputs, reply to information requests by combining stored data, and typically discard constructed replies. It is the first edited volume in AI on this topic, whose many synonyms include `instance-based', `memory-based'. `exemplar-based', and `local learning', and whose topic intersects case-based reasoning and edited k-nearest neighbor classifiers. It is intended for AI researchers and students interested in pursuing recent progress in this branch of machine learning, but, due to the breadth of its contributions, it should also interest researchers and practitioners of data mining, case-based reasoning, statistics, and pattern recognition.
