Bayesian Ontologies in AI Systems - Department of Information and
... are decomposed into parts, and the events and processes in which entities can participate. Ontologies are useful for ensuring that producer and consumer share a common interpretation of data, especially in situations in which ownership boundaries are crossed. Standard representation languages for on ...
... are decomposed into parts, and the events and processes in which entities can participate. Ontologies are useful for ensuring that producer and consumer share a common interpretation of data, especially in situations in which ownership boundaries are crossed. Standard representation languages for on ...
CS 561a: Introduction to Artificial Intelligence
... should eventually succeed. It is a race, but both racers seem to be walking. [John McCarthy] CS 561, Lecture 1 ...
... should eventually succeed. It is a race, but both racers seem to be walking. [John McCarthy] CS 561, Lecture 1 ...
Report of research activities in fuzzy AI and medicine at
... from sensors to feedback procedures based on fuzzy logic, were solved and results incorporated in equipment and related software. Moreover, an experimental arrangement and dedicated software for tremor analysis and feedback for rehabilitation purposes was developed. Non-linear data analysis and a fu ...
... from sensors to feedback procedures based on fuzzy logic, were solved and results incorporated in equipment and related software. Moreover, an experimental arrangement and dedicated software for tremor analysis and feedback for rehabilitation purposes was developed. Non-linear data analysis and a fu ...
CS 561a: Introduction to Artificial Intelligence
... should eventually succeed. It is a race, but both racers seem to be walking. [John McCarthy] CS 561, Lecture 1 ...
... should eventually succeed. It is a race, but both racers seem to be walking. [John McCarthy] CS 561, Lecture 1 ...
Different roles and mutual dependencies of data
... that relate knowledge-based system components to other parts of an integrated system [53, 71]. In order to develop successful methods for this type of integration, a characterization of the things to integrate is needed: How should data, information, and knowledge be characterized so that their diff ...
... that relate knowledge-based system components to other parts of an integrated system [53, 71]. In order to develop successful methods for this type of integration, a characterization of the things to integrate is needed: How should data, information, and knowledge be characterized so that their diff ...
Final Course Review
... • Unlike search techniques, means-ends analysis can select an action even if it is not possible in the current state. • If a planner selects an action that results in the goal state, but is not currently possible, then it will be set as a new goal the conditions necessary for carrying put that actio ...
... • Unlike search techniques, means-ends analysis can select an action even if it is not possible in the current state. • If a planner selects an action that results in the goal state, but is not currently possible, then it will be set as a new goal the conditions necessary for carrying put that actio ...
ppt - IISER Pune
... parts of nervous system RA gradient generated by mesoderm adjacent to neural ...
... parts of nervous system RA gradient generated by mesoderm adjacent to neural ...
Intelligent Software Environment for Integrated Expert Systems
... formalized problems (UF-problems)), are an essential part of a significant number of static and dynamic intelligent systems, as the analysis of development experience [1-6] has shown. At the same time, in conjunction with ES, methods of applied mathematics, soft computing and versatile means of cont ...
... formalized problems (UF-problems)), are an essential part of a significant number of static and dynamic intelligent systems, as the analysis of development experience [1-6] has shown. At the same time, in conjunction with ES, methods of applied mathematics, soft computing and versatile means of cont ...
WSS - cs.uregina.ca - University of Regina
... H.K. Bhargava, D.J. Power, D. Sun, Progress in Web-based decision support technologies, Decision Support Systems, 43(4), 1083-1095, 2007. M. Chen, Y. Liou, C. –W. Wang, Y. W. Fan, Y.-P. J. Chie, TeamSpirit: Design, implementation, and evaluation of a Web-based group decision support system, Decision ...
... H.K. Bhargava, D.J. Power, D. Sun, Progress in Web-based decision support technologies, Decision Support Systems, 43(4), 1083-1095, 2007. M. Chen, Y. Liou, C. –W. Wang, Y. W. Fan, Y.-P. J. Chie, TeamSpirit: Design, implementation, and evaluation of a Web-based group decision support system, Decision ...
Unit 1 : Computer Systems
... 2. Describe the Turing test and explain its rationale 3. Explain the need for a different approach to programming which could represent knowledge 4. Describe simply the development of game playing programs from simple early examples to contemporary complex examples exhibiting intelligence 5. Describ ...
... 2. Describe the Turing test and explain its rationale 3. Explain the need for a different approach to programming which could represent knowledge 4. Describe simply the development of game playing programs from simple early examples to contemporary complex examples exhibiting intelligence 5. Describ ...
Neural communication systems
... between communication units. Communication units are not part of the communication system, and they may participate in communications that are part of different communication systems. Communications are produced according to probabilistic rules depending on earlier communications; these rules are ca ...
... between communication units. Communication units are not part of the communication system, and they may participate in communications that are part of different communication systems. Communications are produced according to probabilistic rules depending on earlier communications; these rules are ca ...
QUICKScan as a quick and participatory methodology for problem
... The actual software development followed an agile approach with a sequence of time-boxed activities: design, develop, test, deliver, elicit feedback and the planning for another iteration (Verweij et al., 2010a,b). After several iterations we’d built enough functionality to start using it in actual ...
... The actual software development followed an agile approach with a sequence of time-boxed activities: design, develop, test, deliver, elicit feedback and the planning for another iteration (Verweij et al., 2010a,b). After several iterations we’d built enough functionality to start using it in actual ...
OpenCog: A Software Framework for Integrative Artificial General
... powerful albeit somewhat speculative vision of modern human intelligence as the integration of components that evolved relatively discretely in prehuman minds. On the other hand, most of the work in the AI field today is far less integrative than what we see in the brain. AI researchers work on indi ...
... powerful albeit somewhat speculative vision of modern human intelligence as the integration of components that evolved relatively discretely in prehuman minds. On the other hand, most of the work in the AI field today is far less integrative than what we see in the brain. AI researchers work on indi ...
Curriculum Vitae - University of Miami School of Business
... Robert Plant is an Associate Professor at the School of Business Administration, University of Miami, Coral Gables, Florida, and holds a Ph.D. in Computer Science. His research, consulting and executive coaching are centered on the CEO/CFO-CIO relationship, the future of technology, and the role of ...
... Robert Plant is an Associate Professor at the School of Business Administration, University of Miami, Coral Gables, Florida, and holds a Ph.D. in Computer Science. His research, consulting and executive coaching are centered on the CEO/CFO-CIO relationship, the future of technology, and the role of ...
Decision support systems - Southeast Missouri State University
... systems (CBIS) play in supporting managers in their semi-structured or unstructured decision-making activities (see DECISION MAKING AND IT/S). Since the 1970s, study of DSS has become an essential part of CBIS. In the 1980s, we witnessed another wave of information technologies, the artificial intel ...
... systems (CBIS) play in supporting managers in their semi-structured or unstructured decision-making activities (see DECISION MAKING AND IT/S). Since the 1970s, study of DSS has become an essential part of CBIS. In the 1980s, we witnessed another wave of information technologies, the artificial intel ...
Issues in Temporal and Causal Inference
... Operation. An operation is an event that can be realized by the system itself. For example, “to follow Bob” is represented in Narsese as operation “⇑f ollow({Bob})”, which the system can realize by directly executing it. The formal definitions of the symbols used above are given in [32], and here th ...
... Operation. An operation is an event that can be realized by the system itself. For example, “to follow Bob” is represented in Narsese as operation “⇑f ollow({Bob})”, which the system can realize by directly executing it. The formal definitions of the symbols used above are given in [32], and here th ...
What Are Ontologies, and Why Do We Need Them?
... very general concepts. This is because, as a rule, different sets of subcategories will result from different criteria for categorization. Two, among many, alternate subcategorizations of the general concept object are physical and abstract, and living and non-living. In some cultures and languages, ...
... very general concepts. This is because, as a rule, different sets of subcategories will result from different criteria for categorization. Two, among many, alternate subcategorizations of the general concept object are physical and abstract, and living and non-living. In some cultures and languages, ...
1997-Efficient Management of Very Large Ontologies
... other capabilities, in this section we describe the overall structure of our approach. The system consists basically of three layers. The lowest level of the system is based on a relational data base management system (RDBMS). This layer manages all I/O operations, as well as some simple relational ...
... other capabilities, in this section we describe the overall structure of our approach. The system consists basically of three layers. The lowest level of the system is based on a relational data base management system (RDBMS). This layer manages all I/O operations, as well as some simple relational ...
Fuzzy Information Approaches to Equipment Condition Monitoring and Diagnosis
... allows propagation of uncertainties along extended chains of reasoning, and eases implementation of large knowledge bases. Several techniques for representing uncertainty in expert systems have been proposed in the AI literature including Bayesian analysis and certainty measures [4]. For the most p ...
... allows propagation of uncertainties along extended chains of reasoning, and eases implementation of large knowledge bases. Several techniques for representing uncertainty in expert systems have been proposed in the AI literature including Bayesian analysis and certainty measures [4]. For the most p ...
mwr-paper.pdf
... “natural” form (e.g., geographical data or text given in natural language). In general, a formal abstraction of the domain being modeled is created which is simple enough to be processed on a computer, but still produces an adequate model of the original information. By evaluating the shortcomings o ...
... “natural” form (e.g., geographical data or text given in natural language). In general, a formal abstraction of the domain being modeled is created which is simple enough to be processed on a computer, but still produces an adequate model of the original information. By evaluating the shortcomings o ...
CV - Department of Artificial Intelligence
... Research Fellowship) are as follows: • I have maintained Edinburgh’s reputation in computational aspects of logic by teaching courses in logic programming and by using logic as a lingua franca for courses in which it is less common (for example in knowledge management and in software engineering). • ...
... Research Fellowship) are as follows: • I have maintained Edinburgh’s reputation in computational aspects of logic by teaching courses in logic programming and by using logic as a lingua franca for courses in which it is less common (for example in knowledge management and in software engineering). • ...
Rīgas Tehniskā universitāte
... specific because they link units of the knowledge unaided and unassisted by humans (supervisors). So the development of the autonomous systems is usually more complex than the development of supervised systems or systems with limited autonomy. The development becomes even more complex if the system ...
... specific because they link units of the knowledge unaided and unassisted by humans (supervisors). So the development of the autonomous systems is usually more complex than the development of supervised systems or systems with limited autonomy. The development becomes even more complex if the system ...
CS 561a: Introduction to Artificial Intelligence
... should eventually succeed. It is a race, but both racers seem to be walking. [John McCarthy] CS 460, Lecture 1 ...
... should eventually succeed. It is a race, but both racers seem to be walking. [John McCarthy] CS 460, Lecture 1 ...
CS 460: Artificial Intelligence
... should eventually succeed. It is a race, but both racers seem to be walking. [John McCarthy] CS 460, Lecture 1 ...
... should eventually succeed. It is a race, but both racers seem to be walking. [John McCarthy] CS 460, Lecture 1 ...
Expert system
In artificial intelligence, an expert system is a computer system that emulates the decision-making ability of a human expert.Expert systems are designed to solve complex problems by reasoning about knowledge, represented primarily as if–then rules rather than through conventional procedural code. The first expert systems were created in the 1970s and then proliferated in the 1980s. Expert systems were among the first truly successful forms of AI software.An expert system is divided into two sub-systems: the inference engine and the knowledge base. The knowledge base represents facts and rules. The inference engine applies the rules to the known facts to deduce new facts. Inference engines can also include explanation and debugging capabilities.