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Michael R. Lowry

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4 papers

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FormaliSE Conference 2014 Conference Paper

Analysis and testing of PLEXIL plans

Jason Biatek
Michael W. Whalen
Mats P. E. Heimdahl
Sanjai Rayadurgam
Michael R. Lowry

Autonomy is increasingly important in missions to remote locations (e.g., space applications and deep sea exploration) since limited bandwidth and communication delays make detailed instructions from a remote base (e.g., Earth or a land base) impractical. The planning systems used for autonomous operation are difficult to verify and validate because they must create plans for use in a specific environment and the correct behavior might not be easy to define.

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AAAI Conference 1988 Conference Paper

Invariant Logic. A Calculus for Problem Reformulation

Michael R. Lowry

Symmetries abound in nature. Observing symmetries often provides the key to discovering internal structure. In problem solving, observing and reasoning about symmetries is a powerful tool for shifting viewpoints on a problem. A calculus for reasoning about problem symmetries has been developed, called Invariant Logic. Invariant Logic is partially implemented in STRATA, a system which synthesizes algorithms through problem reformulation. In STRATA, Invariant Logic is used to reason about generalized problem symmetries for several purposes. The first purpose is as a calculus for generating expressions denoting problem symmetries. The second purpose is problem abstraction - generating abstract problem descriptions which denote models in which the problem symmetries have been collapsed. The third purpose is problem reduction - specializing a problem description by adding constraints in order to realize performance gains.

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AAAI Conference 1987 Conference Paper

Algorithm Synthesis through Problem Reformulation

Michael R. Lowry

AI has been successful in producing expert systems for diagnosis, qualitative simulation, configuration and tutoring-e. g. classification problem solving. It has been less successful in producing expert systems that design artifacts, including computer programs. Deductive synthesis of a design from first principles is combinatorially explosive, yet libraries of design schemas do not have sufficient flexibility for application to novel problems. This paper proposes that the major factor in applying design knowledge is reformulating a problem in terms of the parameters of generic designs. This paper shows how to represent knowledge of generic designs as parameterized theories. This facilitates problem reformulation, making it a well defined search for appropriate parameter instantiations. The representation of design knowledge with parameterized theories is illustrated with generic local search algorithms. The utility of parameterized theories is shown by deriving the simplex algorithm for linear optimization from specification.

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IJCAI Conference 1987 Conference Paper

The Abstraction/Implementation Model of Problem Reformulation

Michael R. Lowry

A good problem representation incorporates important problem constraints while hiding superfluous detail. This paper presents methods for abstracting a problem representation by making implicit problem properties into explicit properties of the representation. The mathematics of the abstraction search space are given in terms of model theory and universal algebra. The Behavioral Abstraction method uses predefined representation maps to lift a problem representation to an abstract theory. The Behavioral Congruence method generates abstract theories and representation maps which incorporate problem constraints expressed as Behavioral Equivalences. Two meta-level methods for generating Behavioral Equivalence theorems are given. The STRATA automatic programming system described in this paper is currently being implemented.

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