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Daniel J. Clancy

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AAAI Conference 1998 Conference Paper

Qualitative Simulation as a Temporally-Extended Constraint Satisfaction Problem

Daniel J. Clancy

qYaditionally, constraint satisfaction problems(CSPs) are characterized using a finite set of constraints expressed within a common, shared constraint language. Whenreasoning across time, however, it is possible to express both temporal and state-based constraints represented within multiple constraint languages. Qualitative simulation provides an instance of this class of CSPin which, traditionally, all solutions to the CSPare computed. In this paper, we formally describe this class of temporally-extended CSPsand situate qualitative simulation within this description. This is followed by a description of the DecSIM algorithm whichis used to incrementally generate all possible solutions to a temporally-extended CSP. DecSIM combines problemdecomposition, a tree-clustering algorithm and ideas similar to directed arc-consistency to exploit structure and causality within a qualitative modelresulting in an exponential speed-up in simulation time whencompared to existing techniques.

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AAAI Conference 1997 Conference Paper

Model Decomposition and Simulation: A Component Based Qualitative Simulation Algorithm

Daniel J. Clancy

Traditionally, qualitative simulation uses a global, state-based representation to describe the behavior of the modeled system. For larger, more complex systems this representation proves extremely inefficient since it provides a complete temporal ordering of all potential distinctions leading to a large, complex behavioral description that obscures relevant distinctions, or even fails to terminate. The model decomposition and simulation algorithm (DecSIM) uses a divide and conquer approach to qualitative simulation. Variables within the system are partitioned into components. Each component is viewed as a separate system and is simulated using a state-based representation limited to the variables within the component. Interactions between components are reasoned about separately. DecSIM provides a promising paradigm for qualitative simulation whose complexity is driven by the complexity of the problem specification rather than the inference mechanism used.

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AAAI Conference 1997 Conference Paper

Static and Dynamic Abstraction Solves the Problem of Chatter in Qualitative Simulation

Daniel J. Clancy

One of the major factors hindering the use of qualitative simulation techniques to reason a, bout the behavior of complex dynamical systems is intractable branching due to a phenomenon called chatter. This paper presents two general abstraction techniques that solve the problem of chatter. Eliminating the problem of chatter significantly extends the range of models that can be tractably simulated using qualitative simulation. Chatter occurs when a variable’s direction of change is constrained only by continuity within a region of the state space. This results in intractable, potentially infinite branching within the behavioral description due to irrelevant distinctions in the direction of change. While a number of techniques have been proposed to eliminate chatter, none of them provide a general solution that can eliminate all instances of chatter. Chatter box abstraction and dynamic chatter abstraction provide two such solutions to this problem. Both solutions eliminate chatter by abstracting the chattering region of the state space into a single qualitative state with an abstract direction of change. The algorithms differ in the manner in which they identify the chattering region of the state space.

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