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Diagrammatic Representation and Reasoning: Some Distinctions
Diagrammatic Representation and Reasoning: Some Distinctions

... representations in general can also have color and texture as part of the representational repertoire, while spatial representations do not seem to involve these properties. Motion is potentially part of all three: diagrams can use animation, and visual and spatial representations can involve sequen ...
Poster - The University of Manchester
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Agency Systems
Agency Systems

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Intro_NN

... – Radial basis function networks – Multi-layer feed forward networks – Recurrent networks (feedback) ...
curriculum vitae - NYU Stern School of Business
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... evolutionary computation techniques such as genetic algorithms. These models take as input histories of data and attempt to reconstruct the psychological and economic forces that drive markets as described by experienced professionals. There are also several specific offshoots from this research, na ...
A Research Perspective: Artificial Intelligence, Management and
A Research Perspective: Artificial Intelligence, Management and

... interaction of AI, management and organiza­ tions. This is an important topic because the success of an AI system depends on the resolution of a variety of technical, managerial and organizational issues; yet academic research is limited. O'Leary and Turban (1987) examined theoretical foundations fo ...
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03 Lecture CSC462

... playing AI does not think about its next move, it is based on the programming it was given, and its moves depend on the moves of the human opponent. • Strong AI is the idea/concept that we will one day create AI that can 'think' i.e. be able to play a chess game that is not based on the moves of the ...
1.1 What is Intelligence?
1.1 What is Intelligence?

... of their fingerprints. We ask him to somehow learn the patterns, which make the five prints distinct in some manner. After having seen the images a several times, that sixth person might get to find something that is making the prints distinct. Things like one of them has fever lines in the print, t ...
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Python Basic

... Python has been slowly but surely gaining more and more fans, and eventually become one of the most popular programming languages in the world. With its clear and elegant syntax, dynamic typing, memory management and advanced libraries, Python makes a great choice for developing applications and scr ...
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Practical Issues in Modeling Large Diagnostic Systems with Multiply

... the set of variables in the other given the set of variables shared by both. It can be shown (Xia97) that this condition holds if and only if nodes shared by the two subnets form a d-sepset, as defined below: Definition 2 Let Di = (Ni , Ei) (i = 0, 1) be two DAGs such that D = D0 t D1 is a DAG. The ...
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Mind, computational theories of

... of individual cells and a ‘scanner’, whose primitive processes consist in registering whether it is scanning a ‘1’ or a ‘0’, and then moving left and right from cell to cell (see Turing machines). This is only one among many possible computational architectures. What is essential to a computer is me ...
BIT5108 - IT Fundamentals
BIT5108 - IT Fundamentals

... Conduct linguistic research, whose aim is to Examination empirical hypotheses about language and make generalisations; Build Natural Language Processing systems (e.g. parsers, thesauri, generators) which differ from traditional rule-based or “symbol-processing” systems in that their core is a statis ...
ARTIFICIAL INTELLIGENCE: THE FUTURE OF COMMAND AND
ARTIFICIAL INTELLIGENCE: THE FUTURE OF COMMAND AND

... on more short-term, commercially viable projects, work aimed at emulating the functioning of the brain still goes on in pure research. These efforts are mainly split into two camps, one approaching the problem from the top down and the other from the bottom up. The top down camp is attempting to rep ...
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... Intelligence In the late 1960's to early 1970's. The basic idea of developing expert systems can be found in the goal of Artificial Intelligence to develop “thinking computers” [12]. The expert system is defined by Bunchanan as computer system in which an attempt is made to capture and render operab ...
Default Reasoning in a Terminological Logic
Default Reasoning in a Terminological Logic

... The field of TLs has lately been an active area of research, with the attention of researchers especially focusing on the investigation of their logical and computational properties. Nevertheless, few researchers have addressed the problem of extending these logics with the ability to perform defaul ...
Development Framework for Qualitative Spatial and Temporal Reasoning Systems
Development Framework for Qualitative Spatial and Temporal Reasoning Systems

... provide strategies for designing a QSTR system based on specific task requirements. This section gives a brief outline of how each of the design principles can be used to drive design. Firstly the developer must decide whether QSTR is applicable to the problem at hand. Considering the task principle ...
How to Grow a Mind: Statistics, Structure, and Abstraction
How to Grow a Mind: Statistics, Structure, and Abstraction

... patterns, h1 and h2; it would be a highly suspicious coincidence to draw three random examples that all fall within the smaller sets h1 or h2 if they were actually drawn from the much larger h3 (18). The prior favors h1 and h3, because as more coherent and distinctive categories, they are more likel ...
The role of Artificial Intelligence Tools in Pharmaceutical Industries
The role of Artificial Intelligence Tools in Pharmaceutical Industries

... Online sessions follow a conversation with a human expert asking focused questions and producing customized recommendations The decision making skills of your top experts can now be made available to everyone through various Expert Systems. Exsys Corvid development software provides non-programmers ...
Normative schemas
Normative schemas

... frames. I strongly believe that it results in most useful theory of norms. It is because such theory operates on frames developed by cognitive science, the science concerning human mind to a largest extent among other disciplines. At the beginning I briefly call the relatively short history of moder ...
Artificial Intelligence and Expert Systems
Artificial Intelligence and Expert Systems

... Expert Systems Versus Knowledge-based Systems Rule-based Expert Systems Frame-based Systems Hybrid Systems Model-based Systems Ready-made (Off-the-Shelf) Systems Real-time Expert Systems ...
Artificial Intelligence - Department of Computing
Artificial Intelligence - Department of Computing

... – Evaluate which of the acquisition methods would be most appropriate in a given situation. – Describe techniques for representing acquired knowledge in a way that facilitates automated reasoning over the knowledge. – Categorise and evaluate AI techniques according to different criteria such as appl ...
Heuristic Classification
Heuristic Classification

... solutions are typically related (Section 4). Another detailed discussion then considers “what gets selected,” possible kinds of solutions (e.g., diagnoses). A taxonomy of problem types is proposed that characterizes solutions of problems in terms of synthesis or analysis of some system in the world ...
Distributed Artificial Intelligence
Distributed Artificial Intelligence

... grasp the fundamental issues and orient them towards relevant research in the area of interest. We discuss key issues related to DAI and classify them into common research areas. We also present an overview of application domains where agents have been used to improve the system performance. 1. Intr ...
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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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