Knowledge Representation, Reasoning, and the Design of Intelligent Agents: The Answer-Set Programming Approach Yulia Kahl » holypet.ru

Yulia Kahl is a member of the Texas Action Group and the Knowledge Representation Lab at Texas Tech. She received her Master’s in Computer Science, focusing on the use of Answer Set Prolog for planning. She has also worked as a programmer at IBM. Mar 10, 2014 · Book Description This in-depth introduction to knowledge representation and reasoning and their use in designing agents for answering logical and probabilistic queries, planning, diagnostics, and other intelligent tasks is based on answer set programming, a powerful knowledge-representation paradigm.

'An excellent text for both students and experts in answer-set programming and knowledge representation.' Chitta Baral - Arizona State University 'Michael Gelfond is one of the creators of answer-set programming, a new programming methodology based on artificial intelligence that has already found several important applications. Jun 03, 2020 · Knowledge Representation, Reasoning, and the Design of Intelligent Agents The Answer-Set Programming Approach by Michael Gelfond and Yulia Kahl. The goal of this site is to provide additional resources for those using the book. Questions can be sent to Yulia Kahl at ygkahl@. Last modified: June 3, 2020. Additions are marked with New. Answer Set Programming ASP Gelfond and Kahl 2014 is a declarative programming language for knowledge representation and reasoning. An ASP problem is expressed in.

Knowledge representation and reasoning is the foundation of artificial intelligence, declarative programming, and the design of knowledge-intensive software systems capable of performing intelligent tasks. Knowledge representation, reasoning, and the design of intelligent agents: the answer-set programming approach / Michael Gelfond, Texas Tech University, Yulia Kahl. pages cm Includes bibliographical references and index. ISBN 978-1-107-02956-9 hardback: alk. paper 1. Intelligent agents Computer software I. Kahl, Yulia, 1970– II. Title.

Knowledge representation and reasoning is the foundation of artificial intelligence, declarative programming, and the design of knowledge-intensive software systems capable of performing intelligent tasks. Using logical and probabilistic formalisms based on answer set programming ASP and action languages, this book shows how knowledge-intensive systems can be given knowledge. Lectures on Artificial Intelligence and Machine Learning, Morgan and Claypool Knowledge Representation, Reasoning, and the Design of Intelligent Agents The Answer-Set Programming Approach by Michael Gelfond and Yulia Kahl Cambridge University Press Leistungsnachweis Exam, assignments, report and talk. 5 Abkürzungen entnehmen Sie bitte Seite 4. 978-1-107-02956-9 - Knowledge Representation, Reasoning, and the Design of Intelligent Agents: The Answer-Set Programming Approach Michael Gelfond and Yulia Kahl.

Answer Set Programming • Solving computational problems by reducing them to computing. • Knowledge Representation, Reasoning, and the Design of Intelligent Agents, by Michael Gelfond and Yulia Kahl, Chapters 2 and 6. Title: Microsoft PowerPoint - Lecture 11 Answer Set Programming. This in-depth introduction to knowledge representation and reasoning and their use in designing agents for answering logical and probabilistic queries, planning, diagnostics, and other intelligent tasks is based on answer set programming, a powerful knowledge-representation paradigm.

An A prolog decision support system for the space shuttle. In Answer Set Programming, Towards Efficient and Scalable Knowledge Representation and Reasoning, Proceedings of the 1st Intl. ASP’01 Workshop, A. Provetti and T. C. Son eds. Apr 19, 2019 · Knowledge Representation, Reasoning, and the Design of Intelligent Agents the Answer-Set Programming Approach. Cambridge University Press, Cambridge. Google Scholar. Gelfond M., Kahl V. Knowledge Representation, Reasoning and the Design of Intelligent Agents. The Answer-Set Programming Approach. Файл формата pdf; размером 1,60 МБ; Добавлен пользователем Евгений Машеров. Request PDF Answer set programming and agents In this paper, we discuss the potential role of answer set programming ASP in the context of approaches to the development of agents and.

Knowledge representation, reasoning, and the design of intelligent agents: the answer-set programming approach. [Michael Gelfond; Yulia Kahl] Home. WorldCat Home About WorldCat Help. Search. Search for Library Items Search for Lists Search for Contacts Search for a Library. M. Gelfond, Y. Kahl: Knowledge Representation, Reasoning, and the Design of Intelligent Agents: The Answer -Set Programming Approach, Cambridge University Press, 2014 4 Artificial Intelligence: Knowledge Representation ©. Mar 10, 2014 · Read "Knowledge Representation, Reasoning, and the Design of Intelligent Agents The Answer-Set Programming Approach" by Michael Gelfond available from Rakuten Kobo. Knowledge representation and reasoning is the foundation of artificial intelligence, declarative programming, and the de.

Select, apply and evaluate a knowledge representation scheme for a specified domain. LO4: Design and implement KR formalisms for a real-world data set. LO5: Interpret, critique and communicate the suitability of data visualisation techniques used in conjunction with the design of KR formalisms and the analysis of the resulting output. Answer Set Programming ASP is a declarative problem solving approach, initially tailored to modeling problems in the area of Knowledge Representation and Reasoning KRR. More recently, its attractive combination of a rich yet simple modeling language with high-performance solving capacities has sparked interest in many other areas even beyond KRR. Answer-Set Programming ASP is one particular manifestation the logic-based approach. I’d like to follow the development of more and more complex agents, from knowledge representation to reasoning such as planning and diagnostics, and show how some traditional problems of AI were solved with this approach. Yulia Kahl College of Charleston.

Knowledge Representation, Reasoning, and the Design of Intelligent Agents: The Answer-Set Programming Approach Yulia Kahl

Michael Gelfond and Yulia Kahl. 2014. Knowledge Representation, Reasoning, and the Design of In-telligent Agents: The Answer-Set Programming Ap-proach. Cambridge University Press. Michael Gelfond and Vladimir Lifschitz. 1988. The Stable Model Semantics for Logic Programming. In International Conference on Logic Programming, pages 1070–1080. Mar 10, 2014 · Lee "Knowledge Representation, Reasoning, and the Design of Intelligent Agents The Answer-Set Programming Approach" por Michael Gelfond disponible en Rakuten Kobo. Knowledge representation and reasoning is the foundation of artificial intelligence, declarative programming, and the de. Answer Set Programming ASP is a declarative problem solving approach, initially tailored to modeling problems in the area of Knowledge Representation and Reasoning KRR. More recently, its attractive combination of a rich yet simple modeling language with high-performance solving capacities has sparked interest in many other areas even. Schaub T Model-based knowledge representation and reasoning via answer set programming Proceedings of the 9th international conference on Functional and logic programming, 1-2 Eiter T, Ianni G, Krennwallner T and Polleres A Rules and Ontologies for the Semantic Web Reasoning Web, 1-53.

Selected Publications. My recent papers can be found in the Papers section of the Knowledge Representation Lab website. M. Balduccini and M. Gelfond: Diagnostic Reasoning with A-Prolog - Theory and Practice of Logic Programming, 34-5:425-461, Jul. 2003 M. Gelfond and N. Leone: Logic Programming and Knowledge Representation – A-Prolog Perspective - Artificial Intelligence, 2002.

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