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Belief closure: A semantics of common knowledge for
Belief closure: A semantics of common knowledge for

... 2. Syntactical definitions and facts The formal language and axiom systems discussed in this paper derive their special features from the fact that there are belief (knowledge) operators B a, one for each individual or 'agent' a, and, even more importantly, a specific operator C to render 'it is com ...
Computational Intelligence
Computational Intelligence

... rules concerning machine tools, a forward-chaining system will generate additional assertions such as “a lathe is power driven” and “a lathe has a tool holder”. Figure 1b details the backward-chaining sequence producing the answer to the query “does a lathe require a power source?”. In the forward c ...
UNIT-6
UNIT-6

... RDBMSs should be obvious. Simple tables of information can be described by Prolog structures, and relationships between tables can be conveniently and easily described by Prolog rules. The retrieval process is inherent in the resolution operation. The goal statements of Prolog provide the queries fo ...
my listing - UBC Computer Science
my listing - UBC Computer Science

... Research Profile: Henri Prade has been working on the handling of uncertainty in artificial intelligence for about twenty-five years, and more particularly on the modeling of different types of reasoning (reasoning under uncertainty, nonmonotonic reasoning and belief revision, similaritybased reason ...
document
document

... ALICE: Just keep talking to me as long as you can. ELIZA: Do you wish to as long as me? ALICE: OK, I will as long as you. ELIZA: Do you wish to will as long as me? ALICE: OK, I will will as long as you. ELIZA: Do you wish to will will as long as me? ALICE: OK, I will will will as long as you. ELIZA: ...
A study note for students
A study note for students

... have detailed explanations and examples, such as undergraduate and MSc level study materials. This is because advanced readings often omit the fundamental and important information – it assumes that you knew it already. ...
Click Here For
Click Here For

...  Introduction to the design of multi degree-of-freedom robots and mobile platforms.  Review of the latest technology available to design robotic systems.  Use of professional engineering tools to design robots.  Programming of microcontrollers to control a robotic system.  Hands-on experience t ...
Introduction to AI ( slides)
Introduction to AI ( slides)

... approach based on logic programming. Participants: Computer Science, Philosophy, Psychology, Linguistics, Engineering, Business, Forestry ...
FLAIRS-30 Uncertain Reasoning Track
FLAIRS-30 Uncertain Reasoning Track

... • Conditional logics, Description logic, Logic programming ...
executive information systems
executive information systems

... customers, suppliers, government Volumes are large Transactions are routine Most common IS systems ...
Knowledge-Based Systems
Knowledge-Based Systems

... User involvement Training Expertise from cooperative experts Qualitative, not quantitative, problem User-friendly interface Expert’s level of knowledge must be high ...
Chapter 10 Intelligent Decision Support Systems
Chapter 10 Intelligent Decision Support Systems

... User involvement Training Expertise from cooperative experts Qualitative, not quantitative, problem User-friendly interface Expert’s level of knowledge must be high ...
Applications of Expert Systems
Applications of Expert Systems

... User involvement Training Expertise from cooperative experts Qualitative, not quantitative, problem User-friendly interface Expert’s level of knowledge must be high ...
Chapter 4 Diagnostic Expert Systems: From Expert`s Knowledge to
Chapter 4 Diagnostic Expert Systems: From Expert`s Knowledge to

... Expert systems found broad application in fault diagnosis from their early stages because an expert system simulates human reasoning about a problem domain, performs reasoning over representations of human knowledge and solves problems using heuristic knowledge rather than precisely formulated relat ...
Information Extraction
Information Extraction

... strings that refer to the same entity and then replacing sets of equivalent strings with canonical entity names. Another approach to handling heterogeneity is to mine”soft matching” rules directly from the “dirty” data extracted from text. ...
Introduction - Bilkent University Computer Engineering Department
Introduction - Bilkent University Computer Engineering Department

... Early enthusiasm, great expectations (1952-1969) • John McCarthy made three crucial contributions in one year, 1958, at MIT – Defined LISP which became the dominant AI programming language – Time sharing is invented – In “Programs with Common Sense” he described Advice Taker, a hypothetical program ...
and Law - The University of Buckingham Press Journals
and Law - The University of Buckingham Press Journals

... de-skilled; others may feel uncomfortable about interacting with computer systems rather than human beings; while still others will lack the confidence to operate any computer system of whatever sort. This question offeasibility is often overlooked by enthusiasts and champions of the field. Yet, fro ...
Advanced Diploma of Computer Systems Technology (ICA60511)
Advanced Diploma of Computer Systems Technology (ICA60511)

... 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 ...
here - ABC Research
here - ABC Research

... characteristics of their interactions); artificial intelligence, particularly knowledge representation and distributed planning and scheduling, in multiple domains including cyber security, intelligence analysis, command and control, information management, decision support, natural language process ...
OpenCogPrime - Ben Goertzel
OpenCogPrime - Ben Goertzel

... contain multiple distinct but interacting types of memory, corresponding to the following types of knowledge: declarative, procedural, sensory, episodic, attentional and intentional. The first four of these memory types are standard in cognitive science [9,10]. Attentional knowledge is knowledge per ...
Advanced Information Technology Based Expert System: Example
Advanced Information Technology Based Expert System: Example

... relevant blocks conditions, its sustainability, and pathology level. Following that, the main task includes determination of ki coefficient meanings connected with model vector equal to patient real anamnesis. The task is successfully performing by usage of genetic algorithms [5]. Step1. Generation ...
Description Logics and Planning - isi
Description Logics and Planning - isi

... flying are both moving actions with specific means of locomotion. Walking is also a moving action that does not require a transportation vehicle. If we describe moving actions in terms of their properties and constraints, they can be organized in a taxonomy and enable more efficient reasoning about ...
RELATED CONFERENCES, CALL FOR PAPERS/PARTICIPANTS
RELATED CONFERENCES, CALL FOR PAPERS/PARTICIPANTS

... twice every three years, the conference provides a medium for exchanging scientific research and technological achievements accomplished by the international community. The scope of ISMIS is intended to represent a wide range of topics on applying Artificial Intelligence techniques to areas as diver ...
JP_springfinal
JP_springfinal

... presents an overview of the field of Natural Language Processing as the basis for a 10week introductory class on the subject matter. The concept for this semester’s independent work stemmed from a previous semester’s independent work. The earlier project entailed the creation of an Internetbased sof ...
AI Intro slides - Cornell Computer Science
AI Intro slides - Cornell Computer Science

... • to perceive, understand, and act • speech recognition and understanding • image understanding (computer vision) B) Reasoning and Planning • modelling the external world • problem solving, planning, and decision making • ability to deal with unexpected problems, uncertainties ...
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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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