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Prof - University of Alberta
Prof - University of Alberta

... of all the models for SP isomorphic. Let us suppose that, though the elements of the intended model of SP are points, they are, instead (as [in 8], the sets of numbers of closed intervals between any two numbers a and b such that aQ and bR, and  is interpreted as “is a proper subset of”. Then, th ...
Diagnosis windows problems based on hybrid intelligence systems
Diagnosis windows problems based on hybrid intelligence systems

... Step 2: Rule extraction process starts for the entire data that has been entered to the expert system, save the rules in a database. The condition of the rule is the error message and the conclusion is a number which refers to a field in the second database. As shown: if D3d9.dll Error Messages then ...
ni.uni-osnabrueck.de - Cognitive Science
ni.uni-osnabrueck.de - Cognitive Science

... on computational models for creativity, concept formation, concept discovery, idea generation, and their overall relation and role to general intelligence as well as researchers focusing on application areas, like computer-aided innovation. Although the different approaches to questions concerning t ...
Improvisation without Representation: Artificial Intelligence and Music
Improvisation without Representation: Artificial Intelligence and Music

... partner’s contribution, but it also avoids a complete mirroring of the human performance. With interactive systems for freely improvised music, as with mobile robots, a full account of expected input is impossible to predict at design time. Any preformed ideas that an improvisor might have going int ...
lesson plan
lesson plan

... Fuzzy Sets – Operations on Fuzzy Sets – Fuzzy Relations – Membership Functions- Fuzzy Rules and Fuzzy Reasoning – Fuzzy Inference Systems – Fuzzy Expert Systems – Fuzzy Decision Making Objective: To impart knowledge on fuzzy logic and different stages in fuzzy systems ...
The Instance Store: DL Reasoning with Large Numbers of Individuals
The Instance Store: DL Reasoning with Large Numbers of Individuals

... two concepts would require DL reasoning (which we are trying to avoid), the optimised iS only checks for syntactic equality using a database lookup. (The chances of detecting equivalence via syntactic checks could be increased by transforming concepts into a syntactic normal form, as is done by opti ...
Challenge
Challenge

...  “The Watson program is already a breakthrough technology in AI. For many years it had been largely assumed that for a computer to go beyond search and really be able to perform complex human language tasks it needed to do one of two things: either it would “understand” the texts using some kind of ...
Curriculum vitae
Curriculum vitae

... was concurrent with, and independent of the work at MIT at that time (by Tom Malone) but to my knowledge there was no other work on this topic at that time or before. Three-level Architecture The article (13) and related articles by some of my students are among the very first publications on the top ...
Complete Issue
Complete Issue

... LogicWeb [9] was developed using SWI-Prolog [11] and the Mosaic web browser for logical programming on the web. A LogicWeb module consists of a graphical user interface (the browser) and a Prolog query processing engine. It is capable of interpreting web pages containing embedded Prolog code. The is ...
Distributed Resolution for Expressive Ontology Networks
Distributed Resolution for Expressive Ontology Networks

... Concerning the reasoning method, analytic tableaux are the dominant method for implementing sound and complete inference systems for description logics [8]. It has been shown, however, that sound and complete resolution methods for expressive description logics can be defined [16, 9]. We exclude oth ...
The Relevance of Artificial Intelligence for Human Cognition
The Relevance of Artificial Intelligence for Human Cognition

... tation: Due to the compositionality principle it is possible to compute the meaning of a complex (logical) expression using the meaning of the embedded subexpressions. On the other hand, it is assumed that neural networks are noncompositional on a principal basis making it difficult to represent co ...
Contextual Reasoning - Homepages of UvA/FNWI staff
Contextual Reasoning - Homepages of UvA/FNWI staff

... general in one situation, is very often – if not always – violated in others. Any statement is true only in a certain context. With a little effort, a more general context can usually be depicted in which the precise form of the statement does not hold anymore. Initial efforts in logic-based AI were ...
Close - IJCAI
Close - IJCAI

... preferences between explanations and model fragments to resolve contradictions and to guide knowledge integration. The system’s knowledge is organized using the knowledgebased network of Friedman and Forbus [2010]. We simulate results from the cognitive science literature concerning the self-explana ...
A Comparative Utility Analysis of Case
A Comparative Utility Analysis of Case

... metric, we want to compute the costs that the system will incur for different problems weighted by the probability that the system will actually encounter those problems. Thus, utility is a function not only of the learned item but also of the learning system, the problem set, and the evaluation met ...
Freelance Graphics
Freelance Graphics

... Reduces logic to an evaluating an expression rather than performing a sequence of steps. ...
slides - Computer Science, NMSU
slides - Computer Science, NMSU

... [1] Rips, L.J., Reasoning, Annual review of psychology, Volume 41, 1990, Pages 321-354. [2] Kurtz, K.J., Genter, D., and Gunn, V., Reasoning, Cognitive Science, 1999, Pages 145-200. [3] Aamodt, A. and Plaza, E., Cased-Based Reasoning: Foundational Issues, Methodological Variations, and System Approa ...
Employing a Java Expert System Shell for Intelligent - CEUR
Employing a Java Expert System Shell for Intelligent - CEUR

... fuzzy logic. The FuzzyJESS toolkit API of JESS allows developers to easily create fuzzy variables, fuzzy sets, fuzzy values and fuzzy rules. Options are provided for specifying which fuzzy inference algorithm will be used to execute the rule. In order to investigate the full potential of fuzzy logic ...
Binding Environmental Sciences and Artificial Intelligence on ECAI`98
Binding Environmental Sciences and Artificial Intelligence on ECAI`98

... Figure 1 shows our interpretation about the above division. The BESAI workshop was an interesting rendezvous between environment scientists and AI engineers that brought to light some of the current AI boundaries in Fig. 1 and gave some ideas about how to extend them. Whereas the traditional softwar ...
Tweety: A Comprehensive Collection of Java
Tweety: A Comprehensive Collection of Java

... bases. Using knowledge bases one can derive new information using either the underlying semantics of the language or a specific reasoner. For example, propositional logic is the most basic form for knowledge representation. Given some set of propositions (or atoms) one can build complex formulas usi ...
Knowledge-Driven Business Intelligence Systems: Part II
Knowledge-Driven Business Intelligence Systems: Part II

... chromosome selection and formulate the problem effectively. ƒ Thus genetic algorithms should be considered at present more as an instrument for scientific research rather than as a tool for generic practical data analysis, for instance, in finance. ...
Repairing Incorrect Knowledge with Model Formulation and
Repairing Incorrect Knowledge with Model Formulation and

... preferences between explanations and model fragments to resolve contradictions and to guide knowledge integration. The system’s knowledge is organized using the knowledgebased network of Friedman and Forbus [2010]. We simulate results from the cognitive science literature concerning the self-explana ...
An Investigation into the Conceptual Controversies between Artificial
An Investigation into the Conceptual Controversies between Artificial

... A system is rational if it does the right thing [19]. The right thing is usually the one which best (or at least well) helps the system in achieving its goals.[19]. In [19], intelligence or rationality is based on subjective and dynamic reasoning rather than the ability to correctly solve problems i ...
An Expert System for Tourist Information Management
An Expert System for Tourist Information Management

... starts learning from user profile, trip database and user historical transactions. The learning process is using a Q-learning technique. The main concept of the system is that users can surf on the PTS web site to find out interesting trips. Then the top five trips are suggested for users after all ...
Cognitive Approach to Creativity Cognitive View of Creativity
Cognitive Approach to Creativity Cognitive View of Creativity

... Cognitive Modeling of Problem Solving: GPS • GPS mimicked human problem solving processes including mistakes • Newell & Simon’s approach developing GPS – Started field of Cognitive ...
The Emergence of Contentful Experience
The Emergence of Contentful Experience

... depend on external support to maintain that stability. A chemical bath, for example, may be maintained in some far-from-equilibrium condition by pumping various solutions into it, and the maintenance of this activity, in turn, depends on the pumps continuing to work and receive power, and the reserv ...
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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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