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Extending the mathematics in qualitative process theory
Author(s) -
D'Ambrosio Bruce
Publication year - 1989
Publication title -
international journal of intelligent systems
Language(s) - English
Resource type - Book series
SCImago Journal Rank - 1.291
H-Index - 87
eISSN - 1098-111X
pISSN - 0884-8173
ISBN - 0-471-60599-9
DOI - 10.1002/int.4550040105
Subject(s) - semantic reasoner , range (aeronautics) , process (computing) , scope (computer science) , mathematics , simple (philosophy) , computer science , task (project management) , dependency (uml) , calculus (dental) , artificial intelligence , epistemology , medicine , philosophy , materials science , management , dentistry , economics , composite material , programming language , operating system
Reasoning about physical systems requires the integration of a range of knowledge and reasoning techniques. P. Hayes has named the enterprise of identifying and formalizing the common‐sense knowledge people use for this task “naive physics.” Qualitative Process theory by K. Forbus proposes a structure and some of the content of naive theories about dynamics, (i.e., the way things change in a physical situation). Any physical theory, however, rests on an underlying mathematics. QP theory assumes a qualitative mathematics which captures only simple topological relationships between values of continuous parameters. While the results are impressive, this mathematics is unable to support the full range of deduction needed for a complete naive physics reasoner. A more complete naive mathematics must be capable of representing measure information about parameter values as well as shape and strength characterizations of the partial derivatives relating these values. This article proposes a naive mathematics meeting these requirements, and shows that it considerably expands the scope and power of deductions which QP theory can perform.