Knowledge Representation and Reasoning
Knowledge representation is at the very core of a radical idea for understanding intelligence. Instead of trying to understand or build brains from the bottom up, its goal is to understand and build intelligent behavior from the top down, putting the focus on what an agent needs to know in order to behave intelligently, how this knowledge can be represented symbolically, and how automated reasoning procedures can make this knowledge available as needed.
This landmark text takes the central concepts of knowledge representation developed over the last 50 years and illustrates them in a lucid and compelling way. Each of the various styles of representation is presented in a simple and intuitive form, and the basics of reasoning with that representation are explained in detail. This approach gives readers a solid foundation for understanding the more advanced work found in the research literature. The presentation is clear enough to be accessible to a broad audience, including researchers and practitioners in database management, information retrieval, and object-oriented systems as well as artificial intelligence. This book provides the foundation in knowledge representation and reasoning that every AI practitioner needs.
*Authors are well-recognized experts in the field who have applied the techniques to real-world problems
* Presents the core ideas of KR&R in a simple straight forward approach, independent of the quirks of research systems
*Offers the first true synthesis of the field in over a decade
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Chapter 2 The Language of FirstOrder Logic
Chapter 3 Expressing Knowledge
Chapter 4 Resolution
Chapter 5 Reasoning with Horn Clauses
Chapter 6 Procedural Control of Reasoning
Chapter 7 Rules in Production Systems
Chapter 8 ObjectOriented Representation
Chapter 9 Structured Descriptions
Chapter 10 Inheritance
abductive actions applicable arity Artiﬁcial Intelligence assume assumption atomic concepts atomic sentences autoepistemic logic belief network calculate called Chapter complete computational conclusions consider constants database deductive reasoning default logic default reasoning deﬁned deﬁnition derivation description logic disjunction domain efﬁciently empty clause entailed example express extension fact ﬁeld Figure ﬁller ﬁnal ﬁnd ﬁnite ﬁre ﬁrst Flies(tweety ﬂuent ﬂy formula given goal Horn clauses individual inﬁnite inheritance input interpretation John knowledge base knowledge representation knowledge-based literals negation negation as failure negative node normal objects planning predicates prime implicates problem procedure PROLOG properties propositional quantiﬁed query Ray Reiter represent representation and reasoning representation language Resolution robot role rule satisﬁes semantics sequence set of clauses situation calculus slot speciﬁc stable expansion subset subsumed subsumption successor state axiom sufﬁcient symbols taxonomy tion TravelStep true Tweety unsatisﬁable variables