Ppt on artificial intelligence in power system

Recursive Self-Improvement, and the World’s Most Important Math Problem Eliezer Yudkowsky Singularity Institute for Artificial Intelligence singinst.org.

Institute for AI The invisible power of human intelligence: Fire Language Nuclear weapons Skyscrapers Spaceships Money Science Eliezer YudkowskySingularity Institute for AI Artificial Intelligence: Messing with the most powerful force in the known universe. Eliezer /A physical system which hits small targets in large search spaces to produce coherent real-world effects. Eliezer YudkowskySingularity Institute for AI "Optimization process": A physical system which hits small targets in large search /


Computing & Information Sciences Kansas State University Monday, 20 Nov 2006CIS 490 / 730: Artificial Intelligence Lecture 37 of 42 Monday, 20 November.

Sciences Kansas State University Monday, 20 Nov 2006CIS 490 / 730: Artificial Intelligence Feedforward ANNs: Representational Power and Bias Representational (i.e., Expressive) Power  Backprop presented for feedforward ANNs with single hidden layer (2-layer// 730: Artificial Intelligence Overfitting in ANNs Other Causes of Overfitting Possible  Number of hidden units sometimes set in advance  Too few hidden units (“underfitting”) ANNs with no growth Analogy: underdetermined linear system of equations /


Topics in Artificial Intelligence: Intelligent Problem Solvers This course is about building systems that can reason -- that is, solve problems by utilizing.

” reasoning. – Learning systems. These posses the ability to expend their knowledge based on the accumulated experience. – Natural language understanding systems. These support dialog in English/French/Japanese/… language. – Game playing systems. – Intelligent robots. Artificial Intelligence Methodologies n Classical problem / the first box from the free-storage list, and deposits new pointers into it. ... Education is power Free storage list University Dotted pairs n Consider the list (A B. C). Here (B. C/


Computing & Information Sciences Kansas State University Friday, 10 Nov 2006CIS 490 / 730: Artificial Intelligence Lecture 33 of 42 Friday, 10 November.

A case study  A taxonomy of learning  Specification of learning problems Issues in Machine Learning  Design choices  The performance element: intelligent systems Some Applications of Learning  Database mining, reasoning (inference/decision support), acting  Industrial usage of intelligent systems Computing & Information Sciences Kansas State University Friday, 10 Nov 2006CIS 490 / 730: Artificial Intelligence Rule and Decision Tree Learning Example: Rule Acquisition from Historical Data Data  Patient/


Artificial Intelligence December 6, 2008 Ail 690.

field as the study and design of intelligent agents, where an intelligent agent is a system that perceives its environment and takes actions which maximize its chances of success.” Artificial Intelligence, Wikipedia, n.d., ¶ 1 In 1956 John McCarthy, the father of / on users legs during activities such as walking or climbing and descending stairs by supporting bodyweight. The motor-powered machine is still at an experimental stage, but elderly people and people undergoing rehabilitation who need support for /


Artificial Intelligence Introduction Chapter. 2 Data Driven Methods What is Artificial Intelligence? Common AI techniques Choosing between AI techniques.

humans – In processing reams of data – Performing complex calculations Powered by DeSiaMore 8 Successful AI applications Targeted tasks more amenable to automated methods – Build special-purpose AI systems Determine appropriate dosage for a drug Classify cells as benign or cancerous – Called “expert systems” Methodology based on expert reasoning Quick and objective ways to obtain answers Powered by DeSiaMore 9 Data Driven Methods What is Artificial Intelligence? Common/


MIT Artificial Intelligence Laboratory — Research Directions Legged Robots Gill Pratt.

Legged Robots Gill Pratt MIT Artificial Intelligence Laboratory — Research Directions Why Do Robot Systems Emphasize Stiff Trajectories Instead of /power if run at high speed, but force/torque is low –Direct drive is too heavy for autonomous robots. –Gears are necessary to multiply force/torque and allow the actuator to run at high speed. –But gears introduce a number of terrible disadvantages … MIT Artificial Intelligence Laboratory — Research Directions Disadvantages of Gear Reduction N 2 increase in/


Introduction to AI and Intelligent Agents Foundations of Artificial Intelligence.

sort of description  Some success with semi-automated methods  Some error detection systems  Automatic program verification Foundations of Artificial Intelligence 18 Some Sub-fields of AI  Language understanding and semantic modeling  One / performance measure, given  the available sensors  the available actuators  the available computing power  the available built-in knowledge Foundations of Artificial Intelligence 30 PEAS Analysis  To design a rational agent, we must specify the task environment/


1 © Copyright 2010 Dieter Fensel, Tobias B ü rger and Ioan Toma Intelligent Systems Introduction.

2010 Dieter Fensel, Tobias B ü rger and Ioan Toma Intelligent Systems Introduction 2 Outline Motivation –What is “Intelligence”? –What is “Artificial Intelligence” (AI)? –Strong AI vs. Weak AI Technical Solution –Symbolic AI vs. Subsymbolic AI –Knowledge-based systems Popular AI systems Subdomains of AI Some relevant people in AI Summary 2 3 MOTIVATION Introduction to Artificial Intelligence 3 4 What is “Intelligence”? "Intelligence denotes the ability of an individual to adapt his/


Artificial Intelligence Computers that think? Artificial Intelligence Computers that think?

systems) Navigation over terrain (Guidance systems) Facial Analyis (Security Systems) Facial Analyis (Security Systems/Artificial Child with Smart Toy in “ AI ” (Can a machine experience “ Love ” ) Machine breeding humans for use as “ battery ” power in “ The Matrix ” So, as you can see…self aware machines can be our friends!!! "I have no hesitation in thinking that a machine can be just as intelligent and just as real as a person, in principle." Professor Rodney Brooks, Director, MIT Artificial Intelligence/


Computing & Information Sciences Kansas State University Monday, 20 Nov 2006CIS 490 / 730: Artificial Intelligence Lecture 37 of 42 Monday, 20 November.

Sciences Kansas State University Monday, 20 Nov 2006CIS 490 / 730: Artificial Intelligence Feedforward ANNs: Representational Power and Bias Representational (i.e., Expressive) Power  Backprop presented for feedforward ANNs with single hidden layer (2-layer// 730: Artificial Intelligence Overfitting in ANNs Other Causes of Overfitting Possible  Number of hidden units sometimes set in advance  Too few hidden units (“underfitting”) ANNs with no growth Analogy: underdetermined linear system of equations /


Michael Arbib CS564 - Brain Theory and Artificial Intelligence, USC, Fall 2001. Lecture 14. FARS and Synthetic PET Michael Arbib: CS564 - Brain Theory.

Artificial Intelligence, USC, Fall 2001. /In a task in/Artificial Intelligence, USC, Fall 2001. Lecture 14. FARS and Synthetic PET PET Results : Precision versus Power Precision versus power/Artificial Intelligence, USC, Fall 2001. Lecture 14. FARS and Synthetic PET Conditional Task versus (Precision, Power) Average Basic Model Assumption Reflected Here:  F2 processes the instruction stimuli only in/Artificial Intelligence, USC, Fall/in/ Brain Theory and Artificial Intelligence, USC, Fall /


605451 Artificial Intelligence Chapter 1 –Part 1 Artificial Intelligence Dr.Hassan Al-Tarawneh.

?, or Avian Influenza? Bunch of academia works ~ who cares? Being God? Artificial (a:tfiil)  “made or produced by man in imitation of something natural”. Intelligence (/intelid3entsie)  “power of learning, understanding & reasoning + mental ability” A.I : for dummies! John McCarthy (1956) “a mechanical system capable to perform actions for human deemed to be intelligent” Elaine Rich (1991) “the science of how to make computer/machine do things/


Latest ECE Projects Ideas In Various Electronics Technologies.

– Electrical Transmission And Distribution Process  Electrical Network Automation & Communication Systems  Remote Data Monitoring & Data Analysis For Power Station  Post Paid Electricity Billing Automation http://www.elprocus.com/ Latest ECE Projects Ideas In Various Electronics Technologies  Power Sharing Of Transformer With Overload Protection  EB Theft Monitoring And Control SystemArtificial Intelligent Solar Tracking System With True Graph & Pc Interface  Petrol Level Indicator http://www/


Eliezer Yudkowsky yudkowsky.net Eliezer Yudkowsky Research Fellow Singularity Institute for Artificial Intelligence yudkowsky.net Yeshiva University March.

arithmetic emerge. Accept unpredictability of complex systems. Eliezer Yudkowsky lesswrong.com Yeshiva University March 2011 Views on Artificial General Addition Neural networks - just like/powerful than human. An AI over some threshold level of intelligence will recursively self-improve and explode into superintelligence. Not all possible agents in mind design space are friendly. If we can obtain certain new insights, it should be possible to construct a benevolent self-improving Artificial Intelligence/


Artificial Intelligence

power of the modern computers, followers of the expert systems approach are designing intelligent machines that solve problems by deductive logic. As the name expert systems suggest, these are machines devoted to solving problems in very specific areas. They have total expertise in/ expert systems. Approaches Swarm Intelligence: This is an approach to, as well as application of artificial intelligence similar to a neural network. Here, programmers study how intelligence emerges in natural systems like swarms/


Lecture 01 – Part A Advanced Artificial Intelligence

be defined as: The capacity to acquire and apply knowledge. The faculty of thought and reason. What is Artificial Intelligence ? Artificial intelligence is the study of systems that act in a way that to any observer would appear to be intelligent. Artificial Intelligence involves using methods based on the intelligent behavior of humans and other animals to solve complex problems. AI is concerned with real-world problems (difficult tasks), which/


ARTIFICIAL INTELLIGENCE [INTELLIGENT AGENTS PARADIGM] Professor Janis Grundspenkis Riga Technical University Faculty of Computer Science and Information.

OF FIRST ORDER LOGIC IN ARTIFICIAL INTELLIGENCE The Role of First-Order Logic In Artificial Intelligence Logic is the oldest form of knowledge representation in a computer. Logic concentrates on using knowledge in a rigorous, provably correct way. Logic representation techniques linked with intelligent systems offer a formal well- founded approach to knowledge representation and reasoning. The Role of First-Order Logic In Artificial Intelligence Logical formalism suggests a powerful way of deriving new/


2005-10-201 Can Artificial Life Engender Real Understanding? Bruce MacLennan Dept. of Computer Science www.cs.utk.edu/~mclennan.

models of cognition provide an alternative More powerful computers permit testing the hypothesis that thought is computation 2005-10-206 The Cognitive Sciences (based on Gardner, 1985) 2005-10-207 Traditional Definition of Artificial IntelligenceArtificial Intelligence (AI) is the part of computer science concerned with designing intelligent computer systems, that is, systems that exhibit the characteristics we associate with intelligence in human behavior — understanding language, learning, reasoning/


Artificial Intelligence

possible to create a computing system that equals human intelligence looking back: over history many things have been considered unique to humans but no longer: tool use; doing mathematics (originally “computer” meant a human doing calculations) why should any current human capabilities in principle be out of bounds for computers? Church’s thesis (paraphrased): there can be no more powerful system that processes information than/


Artificial Intelligence

recommend it. Examining high-level cognition in humans suggests both challenge tasks and ideas for machine intelligence. Moreover, AI systems can serve as computational models of human cognitive processing. This link has produced many of the most powerful ideas in artificial intelligence, including the search metaphor. 6/04/2017 COMPSCI 111/111G - Artificial Intelligence 39 COMPSCI 111/111G - Artificial Intelligence Review of Key Ideas Artificial intelligence is the computational study of structures and/


Chapter 12: Artificial Intelligence and Modeling the Human State

a therapist. In response of ELIZA’s popularity, Weizenbaum wrote a book in 1976: Computer Power and Human Potential. “Science promised man power. But, as so often happens when people are seduced by promises of power… the price/Continuum The Computer Continuum The Computer Continuum Chapter 12 Expert Systems Expert systems are commercially the most successful domain in Artificial Intelligence. These programs mimic the experts in whatever field. Auto mechanic Telephone networking Cardiologist Delivery routing/


Artificial Intelligence Driver Assistant Device (AI-DAD ™)

to Knowledge Elinistech’s Seminars On-site training Education Technology, Performance, Cost Industry leading Bluetooth Lowest power consumption Low BOM costs Silicon Design Acceleration Reedy demo PCB Low cost Chip set Hi value firmware/ in packaging suitable for ultra-compact plug-on modules, or easy integration into embedded auto electronics systems.  The choice delivers solutions that are suitable for all applications - from first-mount to aftermarket products. . All Our Artificial Intelligence platforms/


Michael Arbib CS564 - Brain Theory and Artificial Intelligence, USC, Fall 2001. Lecture 1 Michael Arbib: CS564 - Brain Theory and Artificial Intelligence.

CS564 - Brain Theory and Artificial Intelligence, USC, Fall 2001. Lecture 2 Perceptual And Motor Schemas A perceptual schema embodies the process whereby the system determines whether a given domain of interaction is present in the environment. {Recall /Inhibitory Connection Priming Connection AIP precision-related cell AIP power-related cell Michael Arbib CS564 - Brain Theory and Artificial Intelligence, USC, Fall 2001. Lecture 24 The Problem of Serial Order in Behavior (Karl Lashley) If we tried to learn /


MCA/MSc CS 302 ARTIFICIAL INTELLIGENCE AND EXPERT SYSTEMS

– Bi-directional search For the minimum cost path problem: Uniform cost search We will discuss BFS and DFS in next section. Artificial Intelligence and Expert Systems MCA/MSc III Un-informed Search Techniques Unit-2 Problem Solving Un-informed Search Techniques Breadth-first search (BFS):/It is cold COLD Propositional logic has very limited expressive power e.g. Search a candle in all locality shops has a clear meaning to search all shops in the locality for candle. But propositional logic will require /


Application of Artificial Neural Network and

The term ‘Artificial Intelligence’ was coined by John McCarthy in the Dartmouth Conference in 1956. AI was developed at the initial stages in Laboratories at Princeton, MIT, CMU and Stanford Universities. Artificial Neural Network /. It can be used for various applications, for example in: Image and signal processing; Control systems; Medical diagnosis; Incipient failures detection, diagnosis & prognosis; Power systems reliability; Function Approximations; Speech Processing Corporate Research & Development,/


Computer Systems Lab TJHSST Current Projects 2004-2005 Third Period.

boss artificial intelligence will find the user controlled robot a turn it toward it and walk. 33 Computer Vision: Edge Detections Vertical diff., Roberts, Sobels Computer Vision: Edge Detections Vertical diff., Roberts, Sobels Michael Feinberg Abstract and paper needed 35 Optimization of a Traffic Signal The purpose of this project is to produce an intelligent transport system (ITS) that controls a traffic signal in order/


Artificial Intelligence by Jeff Pasternack Mike Thacker.

can understand English commands in the word of blocks. 1972: Alain Colmerauer writes Prolog 1974: Ted Shortliffe creates MYCIN, the first expert system which showed the effectiveness of/the framework and have the program itself fill in the rest (example: real-time strategy game artificial intelligence run by a neural network that acts based /Very sophisticated—perhaps even sentient—AI may not be far off; with sufficient computation power (such as that offered by quantum computers) it is possible to “evolve” /


Knowledge Acquisition and Modelling

understand, and for someone (who is expert in the specific subject the system is concerned with) to criticise and improve. Its straightforward to implement a production system interpreter. Rete Matching Algorithm Expert Systems Shells Reference - Negnevitsky, Artificial Intelligence: A guide to intelligent systems, 2nd Edition, Addison Wesley Advantages/Disadvantages of production systems ... at first glance Principle disadvantage is their restricted power of expression many useful pieces of knowledge don/


10.1 © 2004 by Prentice Hall Management Information Systems 8/e Chapter 10 Managing Knowledge for the Digital Firm 10 MANAGING KNOWLEDGE FOR THE DIGITAL.

robotics, perceptive systems, expert systems, and intelligent machinesIncludes natural language, robotics, perceptive systems, expert systems, and intelligent machines ARTIFICIAL INTELLIGENCE What is Artificial Intelligence? 10.25 © 2004 by Prentice Hall Management Information Systems 8/e Chapter 10 Managing Knowledge for the Digital Firm Artificial Intelligence:Artificial Intelligence: types of systems that would be able to learn languages and use a perceptual apparatus. –Stores information in active form/


Achieving Advanced Machine Consciousness via Artificial General Intelligence in Virtual Worlds Ben Goertzel, PhD.

patterns/qualia in generally intelligent systems It may be interesting to model these emergent structures using hypersets Artificial General Intelligence versus Narrow AI In Artificial General Intelligence (AGI) “The ability to achieve complex goals in complex environments /synergy and acting on an appropriately powerful knoweldge representation … used to control a system pursuing complex goals … may lead to the emergence of system structures characteristic of general intelligence Why Do I Believe I Can/


Prof. Witold Chmielarz, PhD , Velimir Tasic MSc, Oskar Szumski, PhD

? Requirements of knowledge work systems Substantial computing power for graphics, complex calculations Powerful graphics, and analytical tools /Artificial Intelligence Systems – methods and tools are embeded in a number of KM systems. AI can assist identifiying expertise, eliciting knowledge, interfacing through natural languages intelligent search through intelligent systems (see: Laudon, Laudon, Chapt. 11) Information Technology in KM AI methods used in KM systems may to do the following: Assist in/


Artificial Intelligence

Artificial Real Items Airplanes Birds Silk Flowers Flowers Artificial Snow Snow AI Major Areas - Expert Systems - Natural Language Processor - Speech Recognition - Robotics - Computer Vision - Intelligent Computer-Aided Instruction - Data Mining - Genetic Algorithms Artificial vs. Natural (Human) Intelligence / so it will not be lost. - The expertise is needed in many locations. - The expertise is needed in hostile or hazardous environment. - The system can be used for training. - The ES is more dependable /


 Negnevitsky, Pearson Education, 2002 1 Lecture 1 Introduction to knowledge-base intelligent systems n Intelligent machines, or what machines can do n.

of expertise is evaluated by comparing its performance with the performance of a human expert. n To build an intelligent computer system, we have to capture, organise and use human expert knowledge in some narrow area of expertise.  Negnevitsky, Pearson Education, 2002 12 The history of artificial intelligence n The first work recognised in the field of AI was presented by Warren McCulloch and Walter Pitts/


Artificial Intelligence CSC 361 Prof. Mohamed Batouche Computer Science Department CCIS – King Saud University Riyadh, Saudi Arabia

as: 1. The capacity to acquire and apply knowledge. 2. The faculty of thought and reason. 8 What is Artificial Intelligence ? Artificial intelligence is the study of systems that act in a way that to any observer would appear to be intelligent. Artificial Intelligence involves using methods based on the intelligent behavior of humans and other animals to solve complex problems. AI is concerned with real-world problems (difficult tasks/


1 Chapter 4 Decision Support and Artificial Intelligence Brainpower for Your Business.

How many workers to staff line A What is the EOQ for raw material Z How many turbines to power Lethbridge? Unstructured What are the benefits of merging with XYZ How will consumer react if we lower the price/ is any information that can be shown in map form, such as roads, the distribution of bald eagle populations, and the layout of electrical lines. 11 Geographic Information Systems http://www.corda.com/examples/go/ 12 Artificial Intelligence Artificial intelligence (AI) - the science of making /


G.M.P. OHare University College Dublin Multi-Agent Systems(MAS) &

artificial intelligence there have been many opponents to the whole concept of machines generating anything original. Many objections have been raised. Turing has summarised most of these in his classic paper ‘Computing Machinery and Intelligence’. Theological objection, suggests only the possession of a soul permits thought, hence machine nor animals can think. Mathematical objection, based on Godel’s theorem claims limitations to the power of artificial systems/


Carla P. Gomes CS4700 CS 4700: Foundations of Artificial Intelligence Carla P. Gomes

! The Robbins problem was to determine whether one particular set of rules is powerful enough to capture all of the laws of Boolean algebra. One way to state the Robbins problem in mathematical terms is: Can the equation not(not(P))=P be derived from /Winner of NASAs Software of the Year Award Its one small step in the history of space flight. But it was one giant leap for computer-kind, with a state of the art artificial intelligence system being given primary command of a spacecraft. Known as Remote Agent/


Prof. Witold Chmielarz, PhD , Oskar Szumski, PhD

? Requirements of knowledge work systems Substantial computing power for graphics, complex calculations Powerful graphics, and analytical tools /Artificial Intelligence Systems – methods and tools are embeded in a number of KM systems. AI can assist identifiying expertise, eliciting knowledge, interfacing through natural languages intelligent search through intelligent systems (see: Laudon, Laudon, Chapt. 11) Information Technology in KM AI methods used in KM systems may to do the following: Assist in/


1 Intelligence and Security Informatics for International Security: Information Sharing and Data Mining Hsinchun Chen, Ph.D. McClelland Professor of MIS.

. McClelland Professor of MIS Director, Artificial Intelligence Lab and Hoffman E-Commerce Lab Management Information Systems Department Eller College of Management, University of Arizona 2 A Little Promotion 3 Intelligence and Security Informatics (ISI): Challenges and/World-Wide Web, the Internet and metabolic networks are surprisingly similar in topology (e.g., power-law degree distribution), leading to a conjecture that complex systems are governed by the same self-organizing principle (Albert & Barabasi/


Artificial Intelligence CAP492

, theory and practice of building intelligent entities - Emphasis on system building Scientific point of view: - Use computers as a platform for studying intelligence itself - Emphasis on understanding intelligent behavior. Artificial Intelligence is one of the newest sciences which emerged after the world war II. AI represents a big and open field. The name Artificial Intelligence was adopted for the first time in 1956. (Computational Intelligence) Artificial Intelligence can be viewed as a/


Introduction to Artificial Intelligence

computers to augment human thinking, just as we use motors to augment human or horse power. Robotics and expert systems are major branches of that. The other is to use a computers artificial intelligence to understand how humans think. In a humanoid way. If you test your programs not merely by what they can accomplish, but how they accomplish it, they youre really doing cognitive/


ICT Ethics Bigger Task 2 Aki Heikkinen. What is artificial intelligence?  Artificial intelligence (AI) is an art to duplicate human intelligence for.

to all military and classified intelligence information.  In addition the system is also designed to have capability in quick decision making during critical-situations such as launching nuclear weapon. The case 1: Skynet-effect Questions regarding the case:  How much responsibility can humans give to computer system?  How much power can we give to computer system?  Can be we assurred that the system won’t remove, malform or/


Artificial Intelligence

headings: Search (includes Game Playing). Representing Knowledge and Reasoning with it. Planning. Learning. Natural language processing. Expert Systems. Interacting with the Environment (e.g. Vision, Speech recognition, Robotics) We won’t have time in this course to consider all of these. Some Advantages of Artificial Intelligence more powerful and more useful computers new and improved interfaces solving new problems better handling of information relieves information/


Intelligent Vision Processor “Iolanthe II” rounds Channel Island - Auckland-Tauranga Race, 2007 John Morris Computer Science/ Electrical & Computer Engineering,

neurons can compute in parallel  Vision system (eyes) can exploit this parallelism ~3 x 10 6 sensor elements (rods and cones) in human retina Intelligent Vision  Matching and recognition  Artificial intelligence systems are currently not in the race!/ can resolve these  Active patterns can use IR (invisible, eye-safe) light Artificial Vision Challenges Artificial Vision - Challenges  High processor power  Match parallel capabilities of human brain  Distortion removal  Real lenses always show/


Artificial Intelligence and Computer Games John Laird EECS 494 University of Michigan.

parents Mutation: replace an instruction with a random instruction Genetic Algorithm Evaluation Advantages Powerful optimization technique Can learn novel solutions No examples required to learn Disadvantages “Genetic / in natural and artificial systems, MIT Press 1975. Back: Evolutionary algorithms in theory and practice, Oxford University Press 1996. Booker, Goldberg, & Holland: Classifier systems and genetic algorithms, Artificial Intelligence 40: 235-282, 1989. Rule-based Systems (Production Systems)/


8/27/20151 Sermons From Science -- Aug 2013 科学布道 -- 2013 年 8 月 Sermons from Science is now published in both YouTube under the name “Pastor Chui” and also.

Jawed Vertebrates 8/27/201562 Muscle Power Is Designed, Not Evolutionary 肌肉力量是设计,而不是进化/intelligent design more than the discovery of “quality control”? Your cells employ QC every day. In “How Quality Control Works in Our Cells,” Science Daily described “A cellular control mechanism [that] prevents the production of defective proteins in our cells.” Many genetic diseases are associated with the breakdown of quality control mechanisms, a vital and necessary function for all life, as it is in artificial systems/


Computing & Information Sciences Kansas State University Monday, 21 Aug 2006CIS 490 / 730: Artificial Intelligence Lecture 0 of 42 Monday, 21 August 2006.

practice)  Performance elements: reasoning (inference) and recommender systems Time is Right  Recent progress in algorithms and theory  Rapidly growing volume of online data from various sources  Available computational power  Growth of AI-based industries (e.g., data mining, robotics, web search) Computing & Information Sciences Kansas State University Monday, 21 Aug 2006CIS 490 / 730: Artificial Intelligence Artificial Intelligence: Some Problems and Methodologies Problem Solving  Classical search/


UbiCom Book Slides (Short Version) 1 Ubiquitous computing: smart devices, environments and interaction Chapter 13 Ubiquitous System: Challenges & Outlook.

& Recycling Common Components This can be challenging Consider how we can design common components such as power transformers to be reused. Ubiquitous computing: smart devices, environments and interaction 61 Overview of (Forward)/ cause a difficulty in establishing operational equilibria between multiple active interacting artificial intelligent and physical world systems. Ubiquitous computing: smart devices, environments and interaction 86  AI: Over-Reliance on Computers 2 extremes in portraying a future /


Artificial Intelligence (AI) Lecture 1 CS 362 1. Anmar Abu Hamdah : Dr. Abdul Ahad Siddiqi : Dr. Magdy M Saleh :

any) Co – requisite (if any) TheoryLab CS 362 Intelligent Systems 33-6/3CS 202- Artificial Intelligence CS 362 1.Develop an appreciation of the role of intelligent systems in the contemporary context. 2. Develop a deep understanding of fundamental theoretical and practical concepts about intelligent systems. 3. Develop several applications employing different intelligent system paradigms Course Objectives CS362 Intelligent Systems Artificial Intelligence CS 362 1.Examine the ideas and techniques underlying/


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