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	Knowledge Representation and Reasoning Seminar
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Speaker:	Dr. Pei Wang
                Department of Computer and Information Science
                Temple University
                USA

Topic:		"Non-Axiomatic Reasoning System"

Date:		Friday, July 19, 2002.

Time:		3:00 pm - 4:00pm

Venue: 		Room 3501 (Phase II, via lift 25-26)
		HKUST

Abstract:

A key nature of intelligence is the capacity to work with insufficient
knowledge and resources. However, traditional theory, such as first- order
predicate logic and theory of computation, assume the sufficiency of
knowledge and resources.  Non-Axiomatic Reasoning System (NARS) is an
attempt to re-build the logical foundation of artificial intelligence by
establishing a normative theory of intelligent reasoning under the
assumption of insufficient knowledge and resources.  NARS consists of a
categorical language, an experience-grounded semantics, a set of
syllogism-like inference rules, a dynamic memory structure, and a control
mechanism that is based on resources allocation.  Overall, NARS provides a
unified theory for various types of inference, as well as a unified theory
for reasoning, learning, categorization, planning, memory, association,
attention, creative thinking, high-level perception, problem solving,
decision making, and so on.


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Biography:

Dr. Pei Wang is a Visiting Assistant Professor in the Department of
Computer and Information Sciences, Temple University. He received his
Ph.D. degree in Computer Science and Cognitive Science from Indiana
University in 1995, and his M.S. and B.S. degrees from Peking University
in 1986 and 1983, respectively. Before joined Temple University in 2001,
he did teaching and research work at Peking University, and R&D in US AI
industry.  His research involves many aspects of artificial intelligence
and cognitive science, and has been focused on reasoning with uncertainty,
learning and adaptation, knowledge representation, and real-time decision
making.


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