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2nd International Conference on Hybrid Intelligent Systems
2nd International Conference on Hybrid Intelligent Systems

... Creativity is considered a very human activity and very creative people have always been considered very intelligent or extraordinary people. Traditional Artificial Intelligence (AI) approaches have coped with the problem of implementing computer software able to emulate human intelligence and human ...
Ontology construction for information classification
Ontology construction for information classification

... the ocean of information found in the Internet. This time-consuming hunt, however, makes searching, retrieving, displaying, integrating and maintaining data such arduous tasks. One way to solve this problem is to study the concept behind the Semantic Web in accordance with the principles of ontology ...
The Coinductive Formulation of Common Knowledge
The Coinductive Formulation of Common Knowledge

... associated with knowledge are characterised by S5. In epistemic logic,  is written as K and is interpreted epistemically, that is, K is read “it is known that”. If we want to reason about the knowledge of multiple agents, we can extend S5 by introducing multiple modal operators, each written Ka for ...
Inteligencia Artificial
Inteligencia Artificial

... • Rete networks have been a key component of so-called production systems, which were among the earliest forward chaining systems in widespread use. • The word “production” denotes a condition-action rule. • The steps to solve a problem are described as a chain of deductions. ...
Introduction to Artificial Intelligence
Introduction to Artificial Intelligence

... 1.1.1 What is intelligence, as presumably evidenced by humans? This is a very tough question for anybody to answer, so the first response to this question is to ask why we, as computer scientists, should care about the number of possible answers to this question. The reason that we should care is th ...
My Computer is an Honor Student — but how Intelligent is it?
My Computer is an Honor Student — but how Intelligent is it?

... Strong co-occurrences between sand and surface, grass and race, and gravel and graders (road smoothing machines), throw off information retrieval-based guesses. Rather, a more reliable answer requires knowing that a roller-skate race involves roller skating, that roller skating is on a surface, that ...
Einführung in die Künstliche Intelligenz
Einführung in die Künstliche Intelligenz

... Progress was slower than (unrealistic) expectations ...
course-file-artificial-intelligence
course-file-artificial-intelligence

... Knowledge Representations First order predicate calculus, skolemization, resolution principle & unification, interface mechanisms, horn's clauses, semantic networks, frame systems and value inheritance, scripts, conceptual dependency. UNIT-IV Natural Language processing Parsing techniques, context f ...
Advanced Diploma of Computer Systems
Advanced Diploma of Computer Systems

... This course describes the architecture, components, and operations of routers and switches in a small network. Students learn how to configure a router and a switch for basic functionality. By the end of this course, students will be able to configure and troubleshoot routers and switches and resolv ...
Andrew  Gelsey
Andrew Gelsey

... is a compact symbolic representation of a machine’s long-term behavior which is generated numerically. More recently, I’ve been focusing on the particular problems that arise in trying to embeda computational simulation within a system whose goal is the automated design of complexartifacts. In order ...
Logical Omniscience As Infeasibility - boris
Logical Omniscience As Infeasibility - boris

... normal modal logics yields the possibility of using the semantics of Kripke models, which have proved to be a convenient and intuitively clear tool for reasoning about knowledge, based on the Leibnizian supposition of multiple possible worlds. These postulates, however, have an unrealistic consequen ...
Tim Menzies, Paul Compton Artificial Intelligence Laboratory, School
Tim Menzies, Paul Compton Artificial Intelligence Laboratory, School

... The one exception we are aware of to our general rule of "all non toy-domains are characterised by a lack of data and are therefore vague" is the diagnosis of electrical circuits (Hamscher, Console et al. 1992). Electrical circuits are an artificially constructed domain and it is theoretically possi ...
Agent and Environment - Computer Science and Engineering
Agent and Environment - Computer Science and Engineering

... Agent: anything that perceives and acts on its environment AI: study of rational agents A rational agent carries out an action with the best outcome after considering past and current percepts A rational agent should act so as to maximize performance, given knowledge of the environment ...
CS 561a: Introduction to Artificial Intelligence
CS 561a: Introduction to Artificial Intelligence

... optimize balance between user goals & environment constraints? use reasoning to decide on the best course of action? communicate back with the user? ...
Document
Document

... – most of the existing work has a limitation on reasoning power. – The procedures of the models based on argumentation or logic programs normally lack of necessary game-theoretic properties. ...
as a PDF
as a PDF

... language has the advantage of being much more understandable and easier to read using natural language processing (NLP) algorithms in computer systems. A Controlled Language defines a set of explicit restrictions and constraints on the grammar, lexicon and style of the document being produced. The m ...
NLDB10-OntoGain - Intelligent Systems Laboratory
NLDB10-OntoGain - Intelligent Systems Laboratory

... page}, {print, search}) ...
Expertise transfer and complex problems" using AQUINAS as a
Expertise transfer and complex problems" using AQUINAS as a

... Hierarchies in Aquinas are organized around solutions, traits, knowledge sources (i.e. experts), and cases. Nodes in the four hierarchies combine to form rating grids. In the most simple case, the children of a node in a solution hierarchy supply the solutions along the top of a grid; the children o ...
Chapter 11
Chapter 11

... • Combination of software and hardware that allows the computer to change how it functions or reacts to situations based on feedback it receives • Learning systems software requires feedback on results of actions or decisions • Feedback is used to alter what the system will do in future ...
Knowledge Representation
Knowledge Representation

... Script Components Entry conditions or descriptors of the world that must be true for the script to be called. Results or facts that are true once the ...
What is a plan?
What is a plan?

... the designer into unknown environments, and we show how that role constrains agent design, favoring explicit knowledge representation and reasoning. We treat robotics and vision not as independently defined problems, but as occurring in the service of achieving goals. We stress the importance of the ...
PUFF: An Expert System for Interpretation of
PUFF: An Expert System for Interpretation of

... The PUFF research has demonstrated that if the task, domain, and researchers are carefully matched, then the application of existing techniques can result in a system which successfully performs a moderately complicated task of medical diagnosis. Success of the program can be measured not only in te ...
Creating a Knowledge Base From a Collaboratively Generated
Creating a Knowledge Base From a Collaboratively Generated

... of hyponymic/hyperonymic relations will allow us to compute lexical semantic measures which will further increase the performance of our coreference resolution system, as well as further bringing forward Wikipedia as a direct competitor of manuallydesigned resources such as WordNet. In order to make ...
pdf
pdf

... by means of monitoring, planning, and strategic reasoning. In this domain, strategic reasoning more in particular helps in determining in resource-bounded situations if a go or no go should be given to, or to shift attention to, a certain evaluation of possible plans after an incident. An incident i ...
CH (1) Introduction
CH (1) Introduction

...  The right thing: that which is expected to maximize goal achievement, given the available information  Doesn't necessarily involve thinking – e.g., blinking reflex – but thinking should be in the service of rational action ...
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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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