Artificial Intelligence - Special volume on qualitative reasoning about physical systems
Qualitative reasoning about physical systems
Qualitative reasoning about physical systems
Revised report on the algorithmic language scheme
ACM SIGPLAN Notices
System identification: theory for the user
System identification: theory for the user
Scientific discovery: computational explorations of the creative process
Scientific discovery: computational explorations of the creative process
A stable and efficient algorithm for nonlinear orthogonal distance regression
SIAM Journal on Scientific and Statistical Computing
Practical methods of optimization; (2nd ed.)
Practical methods of optimization; (2nd ed.)
Global optimization
The qualitative process engine
Readings in qualitative reasoning about physical systems
A theory of interactions: unifying qualitative and quantitative algebraic reasoning
Artificial Intelligence - Special issue: Qualitative reasoning about physical systems II
Applied system identification
An Adaptive Nonlinear Least-Squares Algorithm
ACM Transactions on Mathematical Software (TOMS)
A Practical Algorithm for General Large Scale Nonlinear Optimization Problems
SIAM Journal on Optimization
Reasoning about Sensor Data for Automated System Identification
IDA '97 Proceedings of the Second International Symposium on Advances in Intelligent Data Analysis, Reasoning about Data
Parameter Estimation in Chaotic Systems
Parameter Estimation in Chaotic Systems
Numerical Methods for Unconstrained Optimization and Nonlinear Equations (Classics in Applied Mathematics, 16)
Introduction to Global Optimization (Nonconvex Optimization and Its Applications)
Introduction to Global Optimization (Nonconvex Optimization and Its Applications)
Reasoning about nonlinear system identification
Artificial Intelligence
Reasoning about Input-Output Modeling of Dynamical Systems
IDA '99 Proceedings of the Third International Symposium on Advances in Intelligent Data Analysis
Intelligent Sensor Analysis and Actuator Control
IDA '01 Proceedings of the 4th International Conference on Advances in Intelligent Data Analysis
Qualitative simulation and related approaches for the analysis of dynamic systems
The Knowledge Engineering Review
Communicable Knowledge in Automated System Identification
Computational Discovery of Scientific Knowledge
Generalized physical networks for automated model building
IJCAI'99 Proceedings of the 16th international joint conference on Artificial intelligence - Volume 2
Discovering time differential law equations containing hidden state variables and chaotic dynamics
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
SCALETRACK: a system to discover dynamic law equations containing hidden states and chaos
DS'05 Proceedings of the 8th international conference on Discovery Science
| Hi-index | 0.00 |
This paper explores how qualitative information can be used to improve the performance of global optimization procedures. Specifically, we have constructed a nonlinear parameter estimation reasoner (NPER) for finding parameter values that match an ordinary differential equation (ODE) model to observed data. Qualitative reasoning is used within the NPER, for instance, to intelligently choose starting values for the unknown parameters and to empirically determine when the system appears to be chaotic. This enables odrpack, the nonlinear least‐squares solver that lies at the heart of this NPER, to avoid terminating at local extrema in the regression landscape. odrpack is uniquely suited to this task because of its efficiency and stability. The NPER’s robustness is demonstrated via a Monte Carlo analysis of simulated examples drawn from across the domain of dynamics, including systems that are nonlinear, chaotic, and noisy. It is shown to locate solutions for noisy, incomplete real‐world sensor data from radio‐controlled cars used in the University of British Columbia’s soccer‐playing robot project. The parameter estimation scheme described in this paper is a component of pret, an implemented computer program that uses a variety of artificial intelligence techniques to automate system identification – the process of inferring an internal ODE model from external observations of a system – a routine and difficult problem faced by engineers from various disciplines.