Constraint Satisfaction Techniques for Agent-Based Reasoning
Nicoleta Neagu
Sold by preigu, Osnabrück, Germany
AbeBooks Seller since August 5, 2024
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Add to basketSold by preigu, Osnabrück, Germany
AbeBooks Seller since August 5, 2024
Condition: New
Quantity: 5 available
Add to basketConstraint Satisfaction Techniques for Agent-Based Reasoning | Nicoleta Neagu | Taschenbuch | xii | Englisch | 2005 | Birkhäuser | EAN 9783764372170 | Verantwortliche Person für die EU: Springer Basel AG in Springer Science + Business Media, Heidelberger Platz 3, 14197 Berlin, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Constraint satisfaction problems are significant in the domain of automated reasoning for artificial intelligence. They can be applied to the modeling and solving of a wide range of combinatorial applications such as planning, scheduling and resource sharing in a variety of practical domains such as transportation, production, supply-chains, network management and human resource management. In this book we study new techniques for solving constraint satisfaction problems, with a special focus on solution adaptation applied to agent reasoning.
This book presents contributions of mathematicians covering topics from ancient India, placing them in the broader context of the history of mathematics. Although the translations of some Sanskrit mathematical texts are available in the literature, Indian contributions are rarely presented in major Western historical works. Yet some of the well-known and universally-accepted discoveries from India, including the concept of zero and the decimal representation of numbers, have made lasting contributions to the foundation of modern mathematics.
Key topics include:
Ancient Indian Leaps into Mathematics examines these ancient mathematical ideas that were spread throughout India, China, the Islamic world, and Western Europe. Through a systematic approach, it gives an historical account of ancient Indian mathematical traditions and their influence on other parts of the world.
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