Integrating causal reasoning at different levels of abstraction

ABSTRACT

In this paper we describe a problem-solving system which uses a multi-level causal model of its domain. The system functions in the role of a pilot's assistant in the domain of commercial air transport emergencies. The model represents causal relationships among the aircraft subsystems, the effectors (engines, control surfaces), the forces that act on an aircraft in flight (thrust, lift), and the aircraft's flight profile (speed, altitude, etc.). The causal relationships are represented at three levels of abstraction: Boolean, qualitative, and quantitative, and reasoning about causes and effects can take place at each of these levels. Since processing at each level has different characteristics with respect to speed, the type of data required, and the specificity of the results, the problem-solving system can adapt to a wide variety of situations. The system is currently being implemented in the KEE™ development environment on a Symbolics Lisp machine.

REFERENCES

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INDEX TERMS

Primary Classification:
  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE

Additional Classification:
  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
      I.2.3 Deduction and Theorem Proving
          Subjects: Uncertainty, "fuzzy," and probabilistic reasoning
  I.6 SIMULATION AND MODELING

  J. Computer Applications
  J.2 PHYSICAL SCIENCES AND ENGINEERING
      Subjects: Aerospace
  J.7 COMPUTERS IN OTHER SYSTEMS
      Subjects: Command and control

General Terms:
Design, Performance