The National Challenge in Computer Science and Technology (1988) / Chapter Skim
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7 Artificial Intelligence
7 Artificial Intelligence
Pages 51-59
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From page 51... ...
In this chapter, we focus on what we consider to be particularly promising aspects of AT: sensory computing, expert systems, deeper cognitive systems, and robotics. SENSORY COMPUTING Understanding the workings of the human sensory apparatus and implementing comparable capabilities on machines, particularly speech and vision, is an important scientific challenge and a technological imperative.
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From page 52... ...
Advances in natural language understanding and cognitive science, combined with the potential of multiprocessor systems to provide the huge processing power required, hold out a big promise but not a guarantee of expanded capabilities for speech comprehension via computer. Machine vision represents another critical area in which, as in speech, significant progress is likely to depend on the combination of cognitive research with the evolution of massively parallel and most probably special-purpose multiprocessor systems.
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From page 53... ...
Most commonly used are "forward chainings methods, which follow causal paths from conditions presented to the program to conclusions reached by the program (modus pollens applied repeatedly) , or Backward chainings methoafs, which proceed from goal statements to conditions (same logic backward)
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From page 54... ...
In finance, expert systems are used to assist bank officers In deciding the credit worthiness of a loan applicant and to asset insurance underwriters in deciding price and terms for insurance contracts. Probably more than half of today's expert systems are used for diagnostic purposes, such as assisting auto mechanics in diagnosing and repairing subsystems of automobiles and carrying out real-time remote diagnostic tests of massive steam turbine generators.
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From page 55... ...
new machine learning methods for acquiring knowledge based on analogies, on abstractions from internal problem-solving processes, on watching human expert problem solving, and on the automated reading of textual material from journals and textbooks. We can envision that as society changes from industrial to postindustrial and as work becomes increasingly the work of professionals and knowledge workers, the power tools will be expert systems.
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From page 56... ...
DEEPER COGNITIVE SYSTEMS Another unportant focus in Al research involves the attempt to understand and model the deeper cognitive activities fundamental to intelligence, including learning, explaining, planning, and hypothesizing. Research in this area Is an interdisciplinary enterprise, involving a synthesis of concepts from experimental psychology, linguistics, neuroscience, and computer science; advances hold the dual promise of increasing understanding of human cognitive processes and ~ntroducing more and more intelligence into the computer.
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From page 57... ...
Connections systems involve interconnected networks of large numbers of elemental computing nodes that often simply add up the values of their inputs and check if the sum Is above a preset threshold. These massively parallel systems, somet~rnes referred to as neural networks, operate by learning strategies that involve the modification of the elemental nodes (e.g., the thresholds)
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From page 58... ...
A deeper understanding of this integrative process among robot sensors and actuators wild broaden understanding of neuroscience and biomechanics as well.
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From page 59... ...
Some researchers believe that the best hope for progress in planning rests with the creation of more intelligent program tenth a deeper knowledge of the physical world.
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