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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? ...
Artificial intelligence in agriculture
Artificial intelligence in agriculture

... . control issues of precision farming, e.g. site-specific operations, positioning, guidance, weed control, crop protection, management systems, and . energy issues, alternative energy resources in agriculture. Concerning the TC activities, likely new technologies and their applications will come to ...
Artificial Intelligence and Expert Systems
Artificial Intelligence and Expert Systems

... Dalian Dyestuff plant is one of the largest chemical plants in China. It produces about 100 different kinds of dyes and other chemical products. With the economic reform in China, manufacturing decisions were decentralized. The plant managers were suddenly faced with the problem of determining their ...
FD4301939942
FD4301939942

... some forms of cognitive tasking. It is collection of powerful programming techniques studying the nature of home automation. There exist a number of AI tools that make home automation system more sophisticated and that are Rule Based. A rule-based expert system consists of if-then rules that is cond ...
Adaptive Practice of Facts in Domains with Varied Prior Knowledge
Adaptive Practice of Facts in Domains with Varied Prior Knowledge

... developed models are not easily applicable in educational setting, where prior knowledge can be an important factor. There are also many implementations of the spaced repetition principle using “flashcard software” (well known example is SuperMemo), but these implementations usually use scheduling a ...
Choosing between different AI approaches
Choosing between different AI approaches

... A mollusc doesn’t have much consciousness. Reflect upon the extraordinary advances which machines have made during the last few hundred years, and note how slowly the animal and vegetable kingdoms are advancing. The more highly organized machines are creatures not so much of yesterday as of the las ...
How Much AI Does a Cognitive Science Major Need to Know?
How Much AI Does a Cognitive Science Major Need to Know?

... One point to makeimmediately is that cognitive scientists need to have a good understanding of computation in general. If one of the fundamental claims of cognitive science is that the mind is somehowcomputational, then it follows that cognitive scientists need to know about computation. But "comput ...
Intelligent Decision Support Systems- A Framework
Intelligent Decision Support Systems- A Framework

... activities. A properly designed DSS helps decision makers to compile useful information from raw data, documents, personal knowledge, and/or business models to identify and solve problems to make decisions. The early definitions of DSS recognized it as a system intended to support managerial decisio ...
Basic Artificial Intelligence Research at the Georgia Institute of
Basic Artificial Intelligence Research at the Georgia Institute of

... problems: a functional architecture that allows a case-based reasoner to function in a complex, real-world domain and a concrete theory of adaptation. The architecture she is working on incorporates components for the breaking of a problem into parts, the maintaining of consistency between the parts ...
Deciding Intuitionistic Propositional Logic via Translation into
Deciding Intuitionistic Propositional Logic via Translation into

... knowledge stage w1 accessible from w0 with w1 I1 ∧ I2 (and thus w1 I1 as well as w1 I2 ) but w1 6 c. From w1 I1 , i.e. w1 (a ⇒ b) ⇒ c and w1 6 c we obtain the refinement w1 6 a ⇒ b which is indicated by the arrow at w1 in fig. 2. So we need to refine our countermodel by adding another knowledge stag ...
Different roles and mutual dependencies of data
Different roles and mutual dependencies of data

... distinction between artificial and natural systems of this kind. Our focus is on computer systems, although our general discussions will apply to some cognitive models of the human mind as well. In fact, our framework is inspired by influential work in cognitive science ([46], [57]) as well as compu ...
AI and Agents
AI and Agents

... 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 ...
The Promise and Perils of Artificial Intelligence
The Promise and Perils of Artificial Intelligence

... • Knowledge representation is capital to AI • How to model knowledge; how to represented concisely; how to interpret knowledge; and how to provide efficient access and retrieval when needed. • Rule-based, graph-based, logic-based, ontologies, semantic networks, frame representations, concept maps, e ...
logic-based and common
logic-based and common

... In link analysis, we show that behavior of an economic sub-domain can be modeled, approximating an entire domain’s (often unpredictable) behavior. For agent design, our approach to problem decomposition and minimized realization of components has utility, as in the congregation formation of Brooks a ...
Object-based Intelligence in Office and Production Processes: A
Object-based Intelligence in Office and Production Processes: A

... invoked to find an explanation for the exception and the negotiator determines whether the explanation is valid or some information is missing. Each POLYMER activity description contains the following attributes: goal; preconditions; effects (side-effects or secondary effects); decomposition (of an ...
natural language processing system
natural language processing system

... Client-Centered Therapy (CCT), was developed by Carl Rogers in the 40's and 50's and is described as being a "non-directive" approach to counselling. That is, unlike most other forms of counselling, the therapist does not offer treatment, disagree, point out contradictions, or make interpretations o ...
Knowledge Management Process–Perspective on e
Knowledge Management Process–Perspective on e

... through learning cooperation and sharing. Learners conceptualize and offer thoughts along with social communications, which brings opportunity of information exchange through learning externalization and disguise. A group interfaces those learners who offer the same premiums and develops in them the ...
Artificial Intelligence
Artificial Intelligence

... someone is going to get killed or injured. The vehicle will be balancing risk and reward to get you to your destination. You probably want to know how the car values your life. Assuming your self-driving car has some assigned or derived self-value, and assuming that other self-driving cars have the ...
Resources - Department of Computer Science and Engineering
Resources - Department of Computer Science and Engineering

... Society of Mind (Marvin Minsky) ...
Expert Systems - University of Southern California
Expert Systems - University of Southern California

... Inference engines facilitate use of the rule-base. Given the necessary information as to the existing conditions provided by the user, inference engines allow processing of a set of rules to arrive at a conclusion by reasoning through the rule base. For example with the system “if a then b,” and “if ...
project
project

... – How to illustrate the reasoning for each step on the playing board? – Trace the rules that make a cell have only one possibility, color the related cells and give the reasoning ...
From NARS to a Thinking Machine
From NARS to a Thinking Machine

... If we can indeed draw the boundary of “intelligent system” to include normal humans, but not typical animals and computer systems, then the next question is: what is the difference between these two types of system? Hopefully the answer to this question can tell us what intelligence really is. Even ...
PowerPoint Slides - Computer Science Department
PowerPoint Slides - Computer Science Department

... When to Use Expert Systems (continued) • People and organizations should develop an expert system if it can (continued): – Provide expertise needed at a number of locations at the same time or in a hostile environment that is dangerous to human health – Provide expertise that is expensive or rare – ...
Principles of Information Systems, Ninth Edition
Principles of Information Systems, Ninth Edition

... When to Use Expert Systems (continued) • People and organizations should develop an expert system if it can (continued): – Provide expertise needed at a number of locations at the same time or in a hostile environment that is dangerous to human health – Provide expertise that is expensive or rare – ...
experiments in the variety of being - Home page-
experiments in the variety of being - Home page-

... The subject “God” although not dead, e.g. in Christian theology, is taboo in some circles and passé in others; it is something to be avoided. Here are some possible reasons. The discussion focuses on general and academic sentiments c. 2000 in the English speaking world. The first is the idea of sepa ...
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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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