Group 7 ICS 2405
KNOWLEDGE BASED SYSTEMS ASSIGNMENT1 GROUP 7 Peter Karanja Ndung'u Sylvia Indoshi Kasiti – Eric Nyaga Mugo – Hassan Hussein Dima – Linda Aketch
BIT-008-0104/2009 BIT-008-0064/2009 BIT 008-0070/2009 BIT 008-0099/2009
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Group 7 ICS 2405
Outline the modern history of AI Early work in AI focused on using cognitive and biological models to simulate and explain human information processing skills, on "logical" systems that perform commonsense and expert reasoning, and on robots that perceive and interact with their environment. This early work was spurred by visionary funding from the Defense Advanced Research Projects Agency (DARPA) and Office of Naval Research (ONR), which began on a large scale in the early 1960's and continues to this day. Basic AI research support from DARPA and ONR - as well as support from NSF, NIH, AFOSR, NASA, and the U.S. Army beginning in the 1970's - led to theoretical advances and to practical technologies for solving military, scientific, medical, and industrial information processing problems. By the early 1980's an "expert systems" industry had emerged, and Japan and Europe dramatically increased their funding of AI research. In some cases, early expert systems success led to inflated claims and unrealistic expectations: while the technology produced many highly effective systems, it proved very difficult to identify and encode the necessary expertise. The field did not grow as rapidly as investors had been led to expect, and this translated into some temporary disillusionment. AI researchers responded by developing new technologies, including streamlined methods for eliciting expert knowledge, automatic methods for learning and refining knowledge, and common sense knowledge to cover the gaps in expert information. These technologies have given rise to a new generation of expert systems that are easier to develop, maintain, and adapt to changing needs. Today developers can build systems that meet the advanced information processing needs of government and industry by choosing from a broad palette of mature technologies. Sophisticated methods for reasoning about uncertainty and for coping with incomplete knowledge have led to more robust diagnostic and planning systems. Hybrid technologies that combine symbolic representations of knowledge with more quantitative representations inspired by biological information processing systems have resulted in more flexible, human-like behavior. AI ideas also have been adopted by other computer scientists - for example, "data mining," which combines ideas from databases, AI learning, and statistics to yield systems that find interesting patterns in large databases, given only very broad guidelines.
AI is multidisciplinary. Discuss Artificial intelligence (AI) is a multidisciplinary field. It encompasses such diverse fields as computer science, philosophy, and psychology. The aim of AI is to replicate human reasoning and brain activity. The use of AI can improve decision making by enhancing consistency. It helps distribute expertise to non-expert staff. The company retains that expertise even when staff members leave the organization. 2
Group 7 ICS 2405
AI in computer science Artificial Intelligence (AI) is the area of computer science focusing on creating machines that can engage on behaviors that humans consider intelligent. The ability to create intelligent machines has intrigued humans since ancient times and today with the advent of the computer and 50 years of research into AI programming techniques, the dream of smart machines is becoming a reality. Researchers are creating systems which can mimic human thought, understand speech, beat the best human chess player, and countless other feats never before possible. AI in business Today's business world is driven by customer demand. Unfortunately, the patterns of demand vary considerably from period to period. This is why it can be so challenging to develop accurate forecasts. Forecasting is the process of estimating future events, and it is fundamental to all aspects of management. The goals of forecasting are to reduce uncertainty and to provide benchmarks for monitoring actual performance. Emerging information technologies and artificial intelligence (AI) techniques are being used to improve the accuracy of forecasts and thus making a positive contribution to enhancing the bottom line. AI in neuroscience and systems biology The human brain is the best example of intelligence known, with unsurpassed ability for complex, real-time interaction with a dynamic world. Experts have programs designed to develop improved computational models of human cognition that could be used to create improved artificial algorithms for machine perception, reasoning, learning, and intelligence. They are faced with a number of automation challenges, which include creating autonomous systems that can perform reliably without constant human intervention as well as building advanced military intelligence, surveillance, and reconnaissance systems.
Briefly explain any 5 applications of AI 1. Finance Banks Credit card providers, telephone companies, mortgage lenders, banks, and the U.S. Government employ AI systems to detect fraud and expedite financial transactions, with daily transaction volumes in the billions. These systems first use learning algorithms to construct profiles of customer usage patterns, and then use the resulting profiles to detect unusual patterns and take the appropriate action (e.g., disable the credit card). Such automated oversight of financial transactions is an important component in achieving a viable basis for electronic commerce. 2. Diagnosis and treating problems Systems that diagnose and treat problems - whether illnesses in people or problems in hardware and software - are now in widespread use. Diagnostic 3
Group 7 ICS 2405
systems based on AI technology are being built into photocopiers, computer operating systems, and office automation tools to reduce service calls. Standalone units are being used to monitor and control operations in factories and office buildings. AI-based systems assist physicians in many kinds of medical diagnosis, in prescribing treatments, and in monitoring patient responses. Microsoft's Office Assistant, an integral part of every Office 97 application, provides users with customized help by means of decision-theoretic reasoning. 3. Heavy Industry Robots have become common in many industries. They are often given jobs that are considered dangerous to humans. Robots have proven effective in jobs that are very repetitive which may lead to mistakes or accidents due to a lapse in concentration and other jobs which humans may find degrading. General Motors Corporation uses around 16,000 robots for tasks such as painting, welding, and assembly. Japan is the leader in using and producing robots in the world. In 1995, 700,000 robots were in use worldwide; over 500,000 of which were from Japan 4. Aviation Air lines use expert systems in planes to monitor atmospheric conditions and system status. The plane can be put on auto pilot once a course is set for the destination. 5. Music With AI, scientists are trying to make the computer emulate the activities of the skillful musician. Composition, performance, music theory, sound processing are some of the major areas on which research in Music and Artificial Intelligence are focusing.
References: http://www.cs.utexas.edu/users/novak/cs381kcontents.htm http://www-formal.stanford.edu/jmc/whatisai/node3.html http://en.wikipedia.org/wiki/Applications_of_artificial_intelligence http://library.thinkquest.org/2705/
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