Constraint-Based Qualitative Simulation

We consider qualitative simulation involving a finite set of qualitative relations in presence of complete knowledge about their interrelationship. We show how it can be naturally captured by means of constraints expressed in temporal logic and constraint satisfaction problems. The constraints relate at each stage the 'past' of a simulation with its 'future'. The benefit of this approach is that it readily leads to an implementation based on constraint technology that can be used to generate simulations and to answer queries about them.Comment: 10 pages, to appear at the conference TIME 200

Fuzzy qualitative simulation with multivariate constraints

Postprin

Automated simulation as part of a design workstation

A development project for a design workstation for advanced life-support systems (called the DAWN Project, for Design Assistant Workstation), incorporating qualitative simulation, required the implementation of a useful qualitative simulation capability and the integration of qualitative and quantitative simulation such that simulation capabilities are maximized without duplication. The reason is that to produce design solutions to a system goal, the behavior of the system in both a steady and perturbed state must be represented. The Qualitative Simulation Tool (QST), on an expert-system-like model building and simulation interface toll called ScratchPad (SP), and on the integration of QST and SP with more conventional, commercially available simulation packages now being applied in the evaluation of life-support system processes and components are discussed

Causes of Ineradicable Spurious Predictions in Qualitative Simulation

It was recently proved that a sound and complete qualitative simulator does not exist, that is, as long as the input-output vocabulary of the state-of-the-art QSIM algorithm is used, there will always be input models which cause any simulator with a coverage guarantee to make spurious predictions in its output. In this paper, we examine whether a meaningfully expressive restriction of this vocabulary is possible so that one can build a simulator with both the soundness and completeness properties. We prove several negative results: All sound qualitative simulators, employing subsets of the QSIM representation which retain the operating region transition feature, and support at least the addition and constancy constraints, are shown to be inherently incomplete. Even when the simulations are restricted to run in a single operating region, a constraint vocabulary containing just the addition, constancy, derivative, and multiplication relations makes the construction of sound and complete qualitative simulators impossible

Monotone Pieces Analysis for Qualitative Modeling

It is a crucial task to build qualitative models of industrial applications for model-based diagnosis. A Model Abstraction procedure is designed to automatically transform a quantitative model into qualitative model. If the data is monotone, the behavior can be easily abstracted using the corners of the bounding rectangle. Hence, many existing model abstraction approaches rely on monotonicity. But it is not a trivial problem to robustly detect monotone pieces from scattered data obtained by numerical simulation or experiments. This paper introduces an approach based on scale-dependent monotonicity: the notion that monotonicity can be defined relative to a scale. Real-valued functions defined on a finite set of reals e.g. simulation results, can be partitioned into quasi-monotone segments. The end points for the monotone segments are used as the initial set of landmarks for qualitative model abstraction. The qualitative model abstraction works as an iteratively refining process starting from the initial landmarks. The monotonicity analysis presented here can be used in constructing many other kinds of qualitative models; it is robust and computationally efficient

Cellular-Automata Based Qualitative Simulation for Nonprofit Group Behavior

A cellular automata based qualitative simulation of group behavior (referred hitherto as \'loyalty to group\') will be presented by integrating QSIM (Qualitative SIMulation) and CA (Cellular Automata) modeling. First, we provide a breakdown of the structure of a group and offer an analysis of how this structure impacts behavior. The characteristics and impact had by anomalies within a group and by environmental factors are also explored. Second, we explore the transition between cause and effect (referred hitherto as the \'transition rule\') and the change in behavior that is the result of this transition (referred hitherto as the \'successor behavior state\'). A filter for weeding out anomalies is then proposed. The simulation engine is then used integrating all relevant data as outlined above. A concept referred to as the \'Loyalty-cost equilibrium\' is presented and factored into the filter. Third, the validity of this method is tested by running the simulation using eight generalized examples. The input-output of each simulation run using these examples is consistent with what can reasonably be accepted to be true, thus demonstrating that the proposed method is valid. At this point we illustrate how the simulation is applied in context. Simulation outputs (effect on group behavior) at each time stage of two alternating changes in policy are compared to determine which policy would be the most advantageous. This demonstrates that this method serves as reliable virtual tool in the decision making difficulties of group management.Cellular Automata; Qualitative Simulation; Group Behavior; Loyalty-Cost Equilibrium; Loyalty Gravitation; Cost Gravitation

Interactive Semi-Qualitative Simulation

In most virtual worlds, users and agents have limited interactions with the artifacts populating their environment. They can at most operate and sense them with a set of action whose consequences have been predetermined. We propose to extend their range of interaction by introducing interactive semi-qualitative simulation. This would allow them to interactively change the structure of the artifacts and use the simulator\u27s internal models to reason about their behaviors. Virtual prototyping, virtual construction sets, and training systems are direct applications of this technology. In this paper we develop an architecture supporting this concept and report on our current and future implementations

A Note on Competing Merger Simulation Models in Antitrust Cases: Can the Best Be Identified?

Advanced economic instruments like simulation models are enjoying an increased popularity in practical antitrust. There is hope that they – being quantitative predictive economic evidence – can substitute for qualitative structural analysis and lead to unambiguous results. This paper demonstrates that it can be theoretically impossible to identify the most appropriate simulation model for any given merger proposal. Due to the inevitable necessity to reduce real-world complexity and multi-parameter character of merger cases, the comparative fit of proposed merger simulation models with mutually incompatible predictions can be the same. This is valid even if an ideal antitrust procedure is assumed. This insight is important regarding two aspects. First, the scope for partisan economic evidence cannot be completely eroded in merger control. Second, simulation cannot eliminate or substitute for qualitative reasoning and economically informed common sense.merger simulation, merger control, antitrust, economic evidence