Significant advances in artificial intelligence, including machines that play master level chess, or make medical diagnoses, highlight an intriguing paradox. While systems can compete with highly qualified experts in many fields, there has been much less progress in constructing machines that exhibit simple commonsense, the kind expected of any normally intelligent child. As a result, commonsen...

We introduce a uniform non-monotonic framework for knowledge representation based on epistemic logic which is sufficiently general to encompass several nonmonotonic formalisms, including circumscription, autoepistemic logic, various semantics proposed for logic programs and deductive databases (stable semantics, well-founded semantics and stationary semantics) as well as Gelfond’s epistemic spe...

UNLABELLED Every cognitive enterprise involves some form of knowledge representation. Humans represent information about the external world and internal mental states, like beliefs and desires, and use this information to meet goals (e.g., classification or problem solving). Unfortunately, researchers do not have direct access to mental representations. Instead, cognitive scientists design expe...

Knowledge representation and reasoning plays a central role in Artificial Intelligence. Research in Artificial Intelligence (henceforth AI) started off by trying to identify the general mechanisms responsible for intelligent behavior. However, it quickly became obvious that general and powerful methods are not enough to get the desired result, namely, intelligent behavior. Almost all tasks a hu...

The paper describes a system of notions (a T-model) developed for representing temporal information on the semantics -pragmatics level in a natural language understanding system. The choice of the notions to be considered has been relied upon a necessity of special facilities for describing situations with various degrees of detailing according to an inexact character of temporal information in...

Knowledge Representations issues take on special significance in the light of development of the novel Web’s reality that involves the Semantic Web, GRID, P2P and other today’s ITs. In contrast to the previous IT evolution’s stages, the recent one utilizes ontology as separated resource. An elaborate knowledge representation approach implies an efficiency of knowledge-based systems and their in...

The number of knowledge representation (KR) formalisms grows exponentially. What most of those formalisms lack is a successful application. This is particularly true of logic-based KR systems, often created without taking tractability into account. Applied Artificial Intelligence (AI) systems, on the other hand, are often based on one specific formalism claimed to be the one. In this paper we p...

Standard knowledge representation systems are supposed to be able to represent either common or individual knowledge about the world. In this paper we propose an extension to such knowledge representation systems which, in a uniform manner, allows to express beliefs of multiple agents as well as knowledge, desire, time and in fact any modality which has a rst-order predicate logic possible worl...

McIlraith & Allin, CSC384, University of Toronto, Winter 2018 Knowledge Representation (KR) • This material is covered in chapters 7– 9 and 12 (R&N, 3rd ed) (chapters 7—10 (R&N, 2nd ed) ). • Chapter 7 provides useful motivation for logic, and an introduction to some basic ideas. It also introduces propositional logic, which is a good background for first-order logic. • What we cover here is mai...