Commonsense reasoning about causality: Deriving behavior from structure
Artificial IntelligencePublished 1 December 1984
Benjamin Kuipers
Citations520
SJR quartileQ1
SJR score1.84
SNIP3.30
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TL;DR
This paper presents a qualitative-reasoning method for predicting the behavior of mechanisms characterized by continuous, time-varying parameters that can detect a previously unsuspected landmark point at which the system is in stable equilibrium.
Abstract
This paper presents a qualitative-reasoning method for predicting the behavior of mechanisms characterized by continuous, time-varying parameters. The structure of a mechanism is described in terms of a set of parameters and the constraints that hold among them: essentially a ‘qualitative differential equation’. The qualitative-behavior description consists of a discrete set of time-points, at which the values of the parameters are described in terms of ordinal relations and directions of change. The behavioral description, or envisionment, is derived by two sets of rules: propagation rules which elaborate the description of the current time-point, and prediction rules which determine what is known about the next qualitatively distinct state of the mechanism. A detailed example shows how the envisionment method can detect a previously unsuspected landmark point at which the system is in stable equilibrium.
Keywords
Computer Science
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