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ADVANCES IN KNOWLEDGE ACQUISITION AND
ADVANCES IN KNOWLEDGE ACQUISITION AND

... with their stochastic logic. Such an approach provides a practical alternative to richer, yet computationally intractable, approaches to stochastic logics, such as Bayesian networks17. Another emerging approach that lies between these two and is showing promise in a number of domains is Markov logic ...
validation and verification of knowledge bases in the context of
validation and verification of knowledge bases in the context of

... latter is probably caused by the fact, that for many years the majority of information technology applications relate to business, and within its frame to the subject of decision support in the management. At the same time some of the information technologies, mainly those related to the artificial ...
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... …First steps toward connectionist computation and learning ...
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... • Research in AI is concerned with producing machines to automate tasks requiring intelligent behavior. ...
cogsys.aimag12wit - ResearchSpace@Auckland
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... Research in cognitive systems, as represented by contributors to the meeting, differs from what has become mainstream AI in five basic ways. First, it retains a concern with high-level aspects of cognition, such as the ability to engage in multi-step inference, understand the meaning of natural lang ...
PREDICATE LOGIC
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... From 2 and 3: by Modus Ponens, we infer: 4. H From 4: by ^-introduction, we infer: 5. H ^ D From 1 and 5: by Modus Ponens, we infer: 6. R (Goal -- It is raining) ...
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CS 486/686
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... Rationale: The calendar description for the course has become badly out of date. The new description reflects what is currently being taught in the course across all sections and instructors. The prerequisite of (CS 350/354 or ECE 354) is a maturity prerequisiteno material taught in CS 350 is actua ...
Artificial Intelligence and Expert Systems
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... AI is many different sciences and technologies It is a collection of concepts and ideas ...
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Cognitive science
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... information, and knowledge is to be able to make informed, cautious, wise and intelligent decisions.  The decision making process revolves around knowledge and wisdom.  It is through our efforts to understand the nature of knowledge and its evolution to wisdom that we can conceive of, build and im ...
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Artificial Intelligence
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... Programs to do reasoning and to solve problems, diagnosis Modelling an expert: Doctor (diagnose illness), Geologist (discover minerals) We need domain-specific knowledge from a domain expert obtained from an AI specialist ...
Intelligent Systems: Reasoning and Recognition Intelligence
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... In addition, intelligence requires an open universe. 1st order logic is not sufficient. No adequate higher order logics have been found, in general because of the very high cost of knowledge acquisition. More broadly, I would argue that Newel confused "What intelligence is" with "How intelligence is ...
Expert Systems Project Management
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Artificial Intelligence - Tennessee Technological University
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... dullest of men can do. Secondly, even though some machines might do some things as well as we do them, or perhaps even better, they would inevitably fail in others, which would reveal that they are acting not from understanding, but only from the disposition of their organs. For whereas reason is a ...
The History of Artificial Intelligence
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Knowledge Base
Knowledge Base

... Knowledge representation and reasoning Transparency and explanations Ability to communicate Use of huge amounts of knowledge Exploration of huge search spaces Use of heuristics Reasoning with incomplete or conflicting data Ability to learn and adapt ...
The IDP System - Lirias
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... The IDP system consists of two main components: • The grounder reduces a FO(·) theory to an equivalent propositional theory [11]. The grounder combines state-of-the-art grounding technology with a novel symbolic reasoning algorithm to derive which formulas of the propositional theory are certainly t ...
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... The activity of providing such machines as computers with the ability to display behavior that would be regarded as intelligent if it were observed in humans. ...
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... Importance of Alter’s Study Supports concept of developing systems that address particular decisions  Makes clear that DSSs need not be restricted to a particular application type ...
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Knowledge representation and reasoning

Knowledge representation and reasoning (KR) is the field of artificial intelligence (AI) dedicated to representing information about the world in a form that a computer system can utilize to solve complex tasks such as diagnosing a medical condition or having a dialog in a natural language. Knowledge representation incorporates findings from psychology about how humans solve problems and represent knowledge in order to design formalisms that will make complex systems easier to design and build. Knowledge representation and reasoning also incorporates findings from logic to automate various kinds of reasoning, such as the application of rules or the relations of sets and subsets.Examples of knowledge representation formalisms include semantic nets, systems architecture, Frames, Rules, and ontologies. Examples of automated reasoning engines include inference engines, theorem provers, and classifiers.
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