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Automated Modeling for Answering Prediction Questions: Selecting the Time Scale and System Boundary
 IN PROCEEDINGS OF THE TWELFTH NATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE
, 1994
"... The ability to answer prediction questions is crucial to reasoning about physical systems. A prediction question poses a hypothetical scenario and asks for the resulting behavior of variables of interest. Prediction questions can be answered by simulating a model of the scenario. An appropriate syst ..."
Abstract

Cited by 47 (5 self)
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The ability to answer prediction questions is crucial to reasoning about physical systems. A prediction question poses a hypothetical scenario and asks for the resulting behavior of variables of interest. Prediction questions can be answered by simulating a model of the scenario. An appropriate system boundary, which separates aspects of the scenario that must be modeled from those that can be ignored, is critical to achieving a simple yet adequate model. This paper presents an efficient algorithm for system boundary selection, it shows the important role played by the model's time scale, and it provides a separate algorithm for selecting this time scale. Both algorithms have been implemented in a compositional modeling program called tripel and evaluated in the plant physiology domain.
Automated Modeling of Complex Systems to Answer Prediction Questions
 ARTIFICIAL INTELLIGENCE
, 1995
"... ..."
A comprehensive methodology for building hybrid models of physical systems
, 1999
"... This paper describes a comprehensive and systematic framework for building mixed continuous/discrete, i.e., hybrid physical system models. Hybrid models are a natural representation for embedded systems (physical systems with digital controllers) and for complex physical systems whose behavior is si ..."
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Cited by 7 (2 self)
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This paper describes a comprehensive and systematic framework for building mixed continuous/discrete, i.e., hybrid physical system models. Hybrid models are a natural representation for embedded systems (physical systems with digital controllers) and for complex physical systems whose behavior is simplified by introducing discrete transitions to replace fast nonlinear dynamics. In this paper we focus on two classes of abstraction mechanisms, viz., time scale and parameter abstractions, discuss their impact on building hybrid models, and then derive the transition semantics required to ensure that the derived models are consistent with physical system principles. The transition semantics are incorporated into a formal model representation language, which is used to derive a computational architecture for hybrid systems based on hybrid automata. This architecture forms the basis for a variety of hybrid simulation, analysis, and verification algorithms. A complex example of a colliding rod system demonstrates the application of our modeling framework. The divergence of time and behavior analysis principles are applied to ensure that physical principles are not violated in the definition of the discrete transition model. The overall goal is to use this framework as a basis for developing systematic compositional modeling and analysis schemes for hybrid modeling of
HigherOrder Derivative Constraints in Qualitative Simulation
 Artificial Intelligence
, 1991
"... Qualitative simulation is a useful method for predicting the possible qualitatively distinct behaviors of an incompletely known mechanism described by a system of qualitative differential equations (QDEs). Under some circumstances, sparse information about the derivatives of variables can lead to in ..."
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Cited by 7 (3 self)
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Qualitative simulation is a useful method for predicting the possible qualitatively distinct behaviors of an incompletely known mechanism described by a system of qualitative differential equations (QDEs). Under some circumstances, sparse information about the derivatives of variables can lead to intractable branching (or "chatter") representing uninteresting or even spurious distinctions among qualitative behaviors. The problem of chatter stands in the way of real applications such as qualitative simulation of models in the design or diagnosis of engineered systems. One solution to this problem is to exploit information about higherorder derivatives of the variables. We demonstrate automatic methods for identification of chattering variables, algebraic derivation of expressions for secondorder derivatives, and evaluation and application of the sign of second and thirdorder derivatives of variables, resulting in tractable simulation of important qualitative models. Caution is requir...
The Thought Experiment Approach to Qualitative Physics
 Proc. IJCAI89
, 1989
"... This paper discusses the application of the thought experiment methodology to qualitative reasoning. Problem solving using this technique involves simplification of the original problem, solution of the simplified problem, and generalization of the results obtained. Our emphasis in this work is to d ..."
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Cited by 2 (2 self)
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This paper discusses the application of the thought experiment methodology to qualitative reasoning. Problem solving using this technique involves simplification of the original problem, solution of the simplified problem, and generalization of the results obtained. Our emphasis in this work is to demonstrate the effectiveness of this approach in addressing complexity and grain size issues that affect qualitative simulation. The thought experiment methodology is presented formally, the implementation of a problem solver called TEPS is briefly discussed, and the methodology is compared with related techniques such as approximation, aggregation, and exaggeration. 1
Qualitative Analysis of Causal Graphs With Equilibrium TypeTransition
 IN THE PROC. OF IJCAI'97 (NAGOYA
, 1997
"... In this paper, we present a method to qualitatively compute the global characteristics of causal graphs by the analysis of the underlying dynamical systems, rather than traditional qualitative simulations which suffer from intractability and difficulty in understanding their simulation results ..."
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Cited by 2 (2 self)
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In this paper, we present a method to qualitatively compute the global characteristics of causal graphs by the analysis of the underlying dynamical systems, rather than traditional qualitative simulations which suffer from intractability and difficulty in understanding their simulation results. The key idea is to translate a given causal graph into an autonomous dynamical system and to analyze equilibrium points in the system. The method requires no numerical information and it has the advantage of computing the conditions under which a certain equilibrium type holds and when equilibrium typetransitions occur. The
TEPS: The Thought Experiment Approach to Qualitative Physics Problem solving, to appear in
 Recent Advances in Qualitative Physics, B. Faltings and
, 1992
"... This paper discusses the application of the thought experiment methodology to qualitative reasoning. Problem solving using this technique involves simplification of the original problem, solution of the simplifie d problem, and generalization of the results obtained. Our emphasis in this work is to ..."
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Cited by 1 (1 self)
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This paper discusses the application of the thought experiment methodology to qualitative reasoning. Problem solving using this technique involves simplification of the original problem, solution of the simplifie d problem, and generalization of the results obtained. Our emphasis in this work is to demonstrate th e effectiveness of this approach in addressing complexity and grain size issues that affect qualitative simulation. The thought experiment methodology is presented formally, the implementation of a problem solve r called TEPS is briefly discussed, and the methodology is compared with related techniques such as approximation, aggregation, and exaggeration. 1
The paraPC, an analysis
 Proceedings of WoTUG19: Parallel Processing Developments, volume 47 of Concurrent Systems Engineering
, 1996
"... Perturbation analysis deals with the relationships between small changes in a system's inputs or model and changes in its outputs. Reverse simulation is of particular interest, determining how to achieve desired outputs by perturbing inputs or model parameters. Some applications of this type of ..."
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Perturbation analysis deals with the relationships between small changes in a system's inputs or model and changes in its outputs. Reverse simulation is of particular interest, determining how to achieve desired outputs by perturbing inputs or model parameters. Some applications of this type of analysis are suggested. Perturbation analysis is developed in the context of continuous systems whose dynamics, over small ranges of the system's behaviour, can be represented by linear models. All variables and signals are represented by intervals with qualitative end points. Qualitative linear models are introduced to represent timevarying systems. These representations permit the use of network consistency algorithms to solve perturbation analysis problems. This paper is dedicated to the memory of Dr.
How Does Knowledge Discovery Cooperate with Active Database Techniques in Controlling Dynamic Environment?
 in Database and Expert Systems Applications, 5th International Conference DEXA '94
, 1994
"... . A dynamic environment, such as a production process, a communication network, highway traffic, etc., may contain a huge amount of information, changing with time, which is a valuable resource for understanding the general behavior of the environment, discovering the regularities and anomalies ..."
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. A dynamic environment, such as a production process, a communication network, highway traffic, etc., may contain a huge amount of information, changing with time, which is a valuable resource for understanding the general behavior of the environment, discovering the regularities and anomalies currently happening in the environment, controlling an evolution process, and intelligent modeling or managing the environment. Unfortunately, the data generated in a dynamic environment are often expressed in low level primitives and in huge volumes. Because of the dynamic, continuous and rapid changes of the information flow, it is difficult to catch the regularities and anomalies in a dynamic environment and react promptly for realtime applications. In this study, a knowledge discovery technique is integrated with data sampling and active database techniques to discover interesting behaviors of a dynamic environment and react intelligently to the environment changes. The discove...