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Artificial Intelligence: Computers
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The foundations of artificial intelligence are divided into representation, problem-solving methods, architecture, and knowledge. To work on a task, a computer must have an internal representation in its memory, for example, the symbolic description of a room for a moving robot, or a set of features describing a person with a disease. The representation ... includes all the knowledge, including basic programs, for testing and measuring the structure, plus all the programs for transforming the structure into another one in ways appropriate to the task. Changing the representation used for a task can make an immense difference, turning a problem from impossible to trivial.
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Currently, no computers exhibit full artificial intelligence (that is, are able to simulate human behavior). The greatest advances have occurred in the field of games playing. The best computer chess programs are now capable of beating humans. In May, 1997, an IBM super-computer called Deep Blue defeated world chess champion Gary Kasparov in a chess match.
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Understanding intelligence and creating intelligent artifacts, the twin goals of artificial intelligence (AI), represent two of the final frontiers of modern science. Several of the early pioneers of computer science, such as Turing, Von Neumann, and Shannon, were captivated by the idea of creating a form of machine intelligence. The questions and issues considered back then are still relevant today, perhaps even more so.
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The approach of artificial intelligence researchers is largely experimental, with small patches of mathematical theory. As in other experimental sciences, investigators build devices (in this case, computer programs) to carry out their experimental investigations. New programs are created to explore ideas about how intelligent action might be attained, and are ... developed to test hypotheses about concepts or mechanisms involved in intelligent behavior.
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One way the group stays on top of emerging research trends is by sponsoring the region's premier weekly artificial intelligence colloquium. This colloquium covers a broad range of topics and is attended by employees of RightNow Technologies, faculty, researchers, and students from Montana State University, Montana Tech, the University of Montana, other local researchers, and occasionally people from outside our region, including the NSF, NASA, and others. The colloquium has been held at both the corporate headquarters of RightNow Technologies and at the nearby Department of Computer Science at MSU.
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Professor Cherkasov is an expert in computer-aided drug design, in applications of artificial intelligence to structure-activity modeling for bioactive substances and in the development of large-scale bioinformatics and genomics tools and molecular modeling techniques. He is a member of Upstream’s Scientific Advisory Board.
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