Handbook of Knowledge Representation (Foundations of by Frank van Harmelen, Vladimir Lifschitz, Bruce Porter

By Frank van Harmelen, Vladimir Lifschitz, Bruce Porter

Handbook of information Representation describes the basic foundations of data illustration, which lies on the center of man-made Intelligence (AI). The e-book offers an updated evaluation of twenty-five key subject matters in wisdom illustration, written via the leaders of every box. It encompasses a educational historical past and state of the art advancements, in addition to purposes of information illustration in various AI systems.

This guide is prepared into 3 components. half I bargains with normal equipment in wisdom illustration and reasoning and covers such issues as classical common sense in wisdom illustration; satisfiability solvers; description logics; constraint programming; conceptual graphs; nonmonotonic reasoning; model-based challenge fixing; and Bayesian networks. half II makes a speciality of sessions of information and really expert representations, with chapters on temporal illustration and reasoning; spatial and actual reasoning; reasoning approximately wisdom and trust; temporal motion logics; and nonmonotonic causal common sense. half III discusses wisdom illustration in purposes reminiscent of query answering; the semantic net; automatic making plans; cognitive robotics; multi-agent platforms; and information engineering.

This ebook is a necessary source for graduate scholars, researchers, and practitioners in wisdom illustration and AI.

* Make your computing device smarter
* deal with qualitative and unsure information
* enhance computational tractability to resolve your difficulties simply

Show description

Read or Download Handbook of Knowledge Representation (Foundations of Artificial Intelligence) PDF

Best intelligence & semantics books

Numerical Methods for Nonlinear Engineering Models

There are various books at the use of numerical equipment for fixing engineering difficulties and for modeling of engineering artifacts. additionally there are numerous forms of such shows starting from books with a huge emphasis on concept to books with an emphasis on purposes. the aim of this ebook is optimistically to provide a just a little varied method of using numerical tools for - gineering purposes.

Least Squares Support Vector Machines

This ebook makes a speciality of Least Squares aid Vector Machines (LS-SVMs) that are reformulations to plain SVMs. LS-SVMs are heavily with regards to regularization networks and Gaussian tactics but in addition emphasize and take advantage of primal-dual interpretations from optimization thought. The authors clarify the traditional hyperlinks among LS-SVM classifiers and kernel Fisher discriminant research.

The Art of Causal Conjecture (Artificial Intelligence)

In The artwork of Causal Conjecture, Glenn Shafer lays out a brand new mathematical and philosophical starting place for chance and makes use of it to provide an explanation for suggestions of causality utilized in statistics, man made intelligence, and philosophy. a few of the disciplines that use causal reasoning vary within the relative weight they wear protection and precision of data in place of timeliness of motion.

The Autonomous System: A Foundational Synthesis of the Sciences of the Mind

The elemental technology in "Computer technological know-how" Is the technology of idea For the 1st time, the collective genius of the nice 18th-century German cognitive philosopher-scientists Immanuel Kant, Georg Wilhelm Friedrich Hegel, and Arthur Schopenhauer were built-in into sleek 21st-century desktop technology.

Additional info for Handbook of Knowledge Representation (Foundations of Artificial Intelligence)

Example text

The answer to this question is no. From the perspective of knowledge representation, this is an essential limitation, because the concept of transitive closure is the 16 1. Knowledge Representation and Classical Logic mathematical counterpart of the important commonsense idea of reachability. 3 below, one way to overcome this limitation is to turn to second-order logic. 2). If the underlying signature contains the object constants c1 , . . 11) if and only if |I | = {c1I , . . , cnI }. Consider now the signature consisting of the object constant c and the unary function constant f .

In the modified language, the formula in(Paul) will turn into in(Paul, office). Reification makes the language more expressive. p in(x, p). 2. As another example illustrating the idea of reification, compare two versions of the situation calculus. 13) Holds(clear(b1 ), S0 ). 14), clear is a unary function constant. 14) is written in the version of the situation calculus in which (relational) fluents are reified; fluent is the first argument sort of the predicate constant Holds. 1 is the more expressive version, with reified fluents.

X=R ⇒ 14. x = R, ¬in(x) ⇒ 15. x = R, ¬in(x) ⇒ 16. 10) ⇒ 17. 10) ⇒ 18. 19. 3: A proof in first-order logic. 1), the soundness theorem justifies establishing entailment in first-order logic by an object-level argument. 8) follows. This argument is an informal summary of the proof shown in Fig. 3, with the names Paul, Quentin, Robert replaced by P , Q, R. Since proofs in the deductive system described above can be effectively enumerated, from the soundness and completeness of the system we can conclude that the set of logically valid sentences is recursively enumerable.

Download PDF sample

Rated 4.76 of 5 – based on 46 votes