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On John McCarthy`s 80th Birthday, in Honor of his Contributions
On John McCarthy`s 80th Birthday, in Honor of his Contributions

... as constructing a plan to get to the airport. Second, he was proposing using the tools of mathematical logic for proving something other than theorems in mathematical domains. His paper, “Programs With Common Sense” (McCarthy 1959) (often referred to as the Advice-Taker paper), articulated the need ...
Introduction to AI (COMP-424) - McGill School Of Computer Science
Introduction to AI (COMP-424) - McGill School Of Computer Science

... principle be so precisely described that a machine can be made to simulate it. An attempt will be made to find how to make machines use language, form abstractions and concepts, solve kinds of problems now reserved for humans, and improve themselves.” ...
Learning the Past Tense of English Verbs: An Extension to FOIDL
Learning the Past Tense of English Verbs: An Extension to FOIDL

... (ED) ) ) is generated and an identical one is also generated by the generalization of S, then the two frontiers have met, and the concatenation of S and G will be the learnt clause equivalent to the desired Prolog clause. Thus S is producing rules starting from C1 and G is producing rules starting f ...
Faculty of Arts Atkinson College
Faculty of Arts Atkinson College

...  Discuss the relationships between microprocessor component designs and performance  Describe the main types of primary and secondary storage  Distinguish between primary and secondary storage along the dimensions of speed, cost, and capacity  Describe the hierarchy of a computer according to po ...
View PDF - CiteSeerX
View PDF - CiteSeerX

... by controlling the routing of work around the organisation automatically. This is done based on input describing the flow, the decisions, the exceptions, the resource to be used, etc. It co-ordinates user and system participants, together with the appropriate data resources, which may be accessible ...
Devnich Explanation Prospectus
Devnich Explanation Prospectus

... reminiscent of the task that models of analogy typically solve: Analogical inference is the process of using familiar (“source”) knowledge to reason about a novel (“target”) domain (e.g., Gentner, 1983; Holyoak & Thagard, 1995). Second, explainers have a preference for integrating causal information ...
Deploying Multimedia Metadata on the Semantic Web
Deploying Multimedia Metadata on the Semantic Web

... To enable the deployment of existing multimedia metadata formats on the Semantic Web, we advocate the use of the RDF data model [2]. A large number of existing M3 formats have been used for years in diverse applications. Instead of discarding these multimedia metadata standards, we propose a solutio ...
Chapter 02 for Neuro-Fuzzy and Soft Computing
Chapter 02 for Neuro-Fuzzy and Soft Computing

... “AI is the act of making computers do smart things” [Waldrop] ...
Artificial Intelligence
Artificial Intelligence

... then we get 6 to 7 we get 13, then we add 8 to 13 we get 21 and finally if we’ll add 10 to 21 we’ll get 31 as the answer. Again answering the question requires a little bit intelligence. The characteristic of intelligence comes in when we try to solve something, we check various ways to solve it, we ...
events:knowledge-workshop-iros2011:tikanmaki.pdf (340.2 KB)
events:knowledge-workshop-iros2011:tikanmaki.pdf (340.2 KB)

... expanded with new information, new algorithms and new functionalities without making the system too complex to handle? All these questions can be answered, when we can define a general purpose unit for information. Traditionally, research projects around the world have shown too many cases of “reinv ...
Um Provador de Teoremas Multi-Estratégia A Multi
Um Provador de Teoremas Multi-Estratégia A Multi

... system for C1 . We have already developed the rules of this system and soon we will publish them and prove that this C1 KE system is correct and complete. Another possible future work is to develop strategies for the other LFIs presented in [18]. Several LFIs are built there by adding/removing axiom ...
Main Areas of AI
Main Areas of AI

... • If computers control everything --- who controls the computers? • If computers are intelligent what civil rights should be given to computers? • If computers can perform most of our work; what should the human beings do? • Only those things that can be represented in computers are important. • It ...
Deploying Softbots on the World Wide Web
Deploying Softbots on the World Wide Web

... begin with useful softbots deployed on the Web, and issue a promissory note that they will evolve into more intelligent agents. We are still committed to the goal of producing agents that are both intelligent and useful. However, I submit that we are more likely to achieve this conjunctive goal if w ...
PPT - Ubiquitous Computing Lab
PPT - Ubiquitous Computing Lab

... of controversy amongst philosophers (see below). However the subject is grounded, the task of the logician is the same: to advance an account of valid and fallacious inference to allow one to distinguish good from bad arguments. Traditionally, logic is studied as a branch of philosophy. Since the mi ...
Lecture notes for week 6
Lecture notes for week 6

... Some rooms contain a pit into which we fall and perish.  We feel a breeze if near a pit. One room contains a Wumpus that will eat us.  We have one arrow that we can shoot in the direction we are facing.  We smell a stench if near the Wumpus. Somewhere, there is a pot of gold. ...
Introduction
Introduction

... Walmart – PoS data  future purchases Collaborative filtering Many, many more ...
Intelligence decision systems in enterprise information management
Intelligence decision systems in enterprise information management

... used in variety of applications with great success. Artificial neural network (ANN) models take inspiration from the basic framework of the brain. The main parts of a neuron are cell body, axon and dendrites. A signal transport from axon to dendrites and passing through other neurons by synapses (Fu ...
CS2351 ARTIFICIAL INTELLIGENCE Ms. K. S. GAYATHRI
CS2351 ARTIFICIAL INTELLIGENCE Ms. K. S. GAYATHRI

... Logical agents – propositional logic – inferences – first-order logic – inferences in firstorder logic – forward chaining – backward chaining – unification – resolution Objective: To illustrate the basic concepts of logic and knowledge-based agents and to discuss the representation of knowledge and ...
Pedagogical Possibilities for the N-Puzzle Problem
Pedagogical Possibilities for the N-Puzzle Problem

... implementation language for search algorithms (and for other techniques too) is LISP. However our preference for this project is Prolog due to the following reasons: • The Prolog code is very concise and easily understood by students because of the language declarative nature. The authors’ experienc ...
MULTIPLE-AGENT PLANNING  SYSTEMS Kurt  Konolige Nils  J.  Nilsson
MULTIPLE-AGENT PLANNING SYSTEMS Kurt Konolige Nils J. Nilsson

... Thus, each agent must represent not only the usual information about objects in the world and the preconditions and effects of its own actions, but it must also represent and reason about what other agents We describe a believe and what they may do. planning system t??at address es these is sues and ...
Artificial Intelligence and Environmental Decision Support Systems
Artificial Intelligence and Environmental Decision Support Systems

... variables involved, and a list of possible models. The next step is to select a set of methods and models that cover all kinds of knowledge and functionalities needed for the decision-making process. Once the models are selected, they must be fully implemented by means of machine learning, data mini ...
ch09 - Dr Ebrahimi . com
ch09 - Dr Ebrahimi . com

...  Computer support for structured decisions is for each structured decision, prescribed solutions have been developed through the use of mathematical functions. This approach is called management science or operations research. Copyright 2007 John Wiley & Sons, Inc. ...
A Flexible Interface for Linking Applications to Penman`s Sentence
A Flexible Interface for Linking Applications to Penman`s Sentence

... grammar is capable of expressing far more delicate shades of meaning than a particular application may require. Rather than require that the application repeatedly specify all the necessary inquiry responses to generate some grammatical phenomenon, Penman makes it possible to use macros to abbreviat ...
The CLARION Cognitive Architecture: A Tutorial
The CLARION Cognitive Architecture: A Tutorial

... •" Psychologically oriented cognitive architectures: “intelligent” systems that are cognitively realistic; detailed cognitive theories that have been tested through capturing and explaining psychological data; and so on ! •" They help to shed new light on human cognition and therefore they are usefu ...
Diagnosis of Pulmonary Embolism Using Fuzzy Inference System
Diagnosis of Pulmonary Embolism Using Fuzzy Inference System

... • Despite its name Fuzzy Logic is not nebulous, cloudy or vague. • It provides a very precise approach for dealing with uncertainty which is derived from complex human behavior. • Fuzzy Logic is so powerful, mainly because it does not require a deep understanding of a system or exact and precise num ...
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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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