PYTHIA: A Knowledge-Based System to Select Scientific Algorithms

ACM Transactions on Mathematical Software

Volumn 22, Issue 4, 1996, Pages 447-468

  Weerawarana, Sanjiva ^a,d   Houstis, Elias N ^a,d   Rice, John R ^a,d   Joshi, Anupam ^b,e   Houstis, Catherine E ^c  

^a PURDUE UNIVERSITY   (United States)

^b UNIVERSITY OF MISSOURI   (United States)

^c UNIVERSITY OF CRETE   (Greece)

^d Purdue University   (United States)

^e University of Missouri   (United States)

Author keywords

Algorithms; Computational intelligence; G.1.8 Numerical Analysis : Partial Differential Equations; I.2.1 Artificial Intelligence : Applications and Expert Systems; Knowledge based systems; Partial differential equations; Performance

Indexed keywords

ALGORITHMS; ARTIFICIAL INTELLIGENCE; COMPUTATIONAL COMPLEXITY; DIGITAL ARITHMETIC; NATURAL SCIENCES COMPUTING; NUMERICAL ANALYSIS; PARAMETER ESTIMATION; PARTIAL DIFFERENTIAL EQUATIONS;

PROBLEM SOLVING ENVIRONMENTS (PSES); PYTHIA KNOWLEDGE BASED SYSTEMS;

EXPERT SYSTEMS;

EID: 0030381078     PISSN: 00983500     EISSN: None     Source Type: Journal    
DOI: 10.1145/235815.235820     Document Type: Article

References (30)

1. BAREISS, R. 1986. Exemplar-Based Knowledge Analysis. Academic Press, New York.
2. BOISVERT, R. F., RICE, J. R., AND HOUSTIS, E. N. 1979. A system for performance evaluation of partial differential equations software. IEEE Trans. Softw. Eng. SE-5, 4, 418-425.
3. CARPENTER, G. A. AND GROSSBERG, S. 1988. The art of adaptive pattern recognition by a self-organizing neural network. Computer 21, 77-88.
4. DURBIN, R. AND WILLSHAW, D. 1987. An analogue approach to the travelling salesman problem using an elastic net method. Nature 326, 689-691.
5. DYKSEN, W. R., AND GRITTER, C. R. 1989. Elliptic expert: An expert system for elliptic partial differential equations. Math. Comput. Simul. 31, 333-343.
6. DYKSEN, W. R. AND GRITTER, C. R. 1992. Scientific computing and the algorithm selection problem. In Expert Systems for Scientific Computing, E. N. Houstis, J. R. Rice, and R. Vichnevetsky, Eds. North-Holland, Amsterdam, 19-31.
7. DYKSEN, W. R., RIBBENS, C. J., AND RICE, J. R. 1988. The performance of numerical methods for elliptic problems with mixed boundary conditions. Num. Meth. Partial Differential Equations 4, 347-361.
8. GALLOPOULOS, E., HOUSTIS, E. N., AND RICE, J. R. 1994. Problem-solving environments for computational science. IEEE Comput. Sci. Eng. 1, 11-23.
9. GIARRATANO, J. C. 1991. CLIPS User's Guide. Ver. 5.1. NASA Lyndon B. Johnson Space Center, Houston, Tex.
10. HOLLANDER, M. AND WOLFE, D. 1973. Nonparametric Statistical Methods. John Wiley and Sons, New York.
11. HOPFIELD, J. J. AND TANK, D. 1986. Computing with neural circuits. Science 233, 625-633.
12. HOUSTIS, E. N. AND RICE, J. R. 1982. High order methods for elliptic partial differential equations with singularities. Int. J. Num. Meth. Eng. 18, 737-754.
13. HOUSTIS, E. N., RICE, J. R., CHRISOCHOIDES, N. P., KARATHANASIS, H. C., PAPACHIOU, P. N., SAMARTZIS, M. K., VAVALIS, E. A., WANG, K. Y., AND WEERAWARANA, S. 1990. //ELLPACK: A numerical simulation programming environment for parallel MIMD machines. In Proceedings of Supercomputing '90. ACM Press, New York, 96-107.
14. HOUSTIS, E. N., RICE, J. R., CHRISTARA, C. C., AND VAVALIS, E. A. 1988. Performance of scientific software. In Mathematical Aspects of Scientific Software, J. R. Rice, Ed. Springer-Verlag, Berlin, 123-155.
15. JOSHI, A., WEERAWARANA, S., AND HOUSTIS, E. N. 1994. The use of neural networks to support "intelligent" scientific computing. In Proceedings of the International Conference on Neural Networks, World Congress on Computational Intelligence. Vol. IV. 411-416.
16. JOSHI, A., WEERAWARANA, S., RAMAKRISHNAN, N., HOUSTIS, E., AND RICE, J. 1996. Neurofuzzy support for problem solving environments. IEEE Comput. Sci. Eng. 3.
17. KAMEL, M. S., MA, K. S., AND ENRIGHT, W. H. 1993. ODEXPERT: An expert system to select numerical solvers for initial value ODE systems. ACM Trans. Math. Softw. 19, 1 (Mar.), 44-62.
18. KONIG, S. AND ULLRICH, C. 1990. An expert system for the economical application of self-validating methods for linear equations. In Intelligent Mathematical Software Systems, E. N. Houstis, J. R. Rice, and R. Vichnevetsky, Eds. North-Holland, Amsterdam, 195-220.
19. MOORE, P. K., OZTURAN, C., AND FLAHERTY, J. E. 1990. Towards the automatic numerical solution of partial differential equations. In Intelligent Mathematical Software Systems, E. N. Houstis, J. R. Rice, and R. Vichnevetsky, Eds. North-Holland, Amsterdam, 15-22.
20. PEARL, J. 1988. Probabilistic Reasoning in Intelligent Systems: Networks of Plausible Inference. Morgan Kaufmann, San Mateo, Calif.
21. RICE, J. R. 1976. The algorithm selection problem. Adv. Comput. 15, 65-118.
22. RICE, J. R. 1979. Methodology for the algorithm selection problem. In Performance Evaluation of Numerical Software, L. D. Fosdick, Ed. North-Holland, Amsterdam, 301-307.
23. RICE, J. R. AND BOISVERT, R. F. 1985. Solving Elliptic Problems Using ELLPACK. Springer-Verlag, Berlin.
24. RICE, J. R., HOUSTIS, E. N., AND DYKSEN, W. R. 1981. A population of linear, second order, elliptic partial differential equations on rectangular domains, part I. Math. Comput. 36, 475-484.
25. RUMELHART, D. E. AND MCCLELLAND, J. L. 1986. Parallel Distributed Processing, Explorations into the Microstructure of Cognition. MIT Press, Cambridge, Mass.
26. SIU, K. Y., ROYCHOWDHURY, V., AND KALATH, T. 1995. Discrete Neural Computation. Prentice-Hall, Englewood Cliffs, N.J.
27. WEERAWARANA, S. 1994. Problem solving environments for partial differential equation based applications. Ph.D. thesis, Dept. of Computer Sciences, Purdue Univ., West Lafayette, Ind.
28. WEERAWARANA, S., HOUSTIS, E. N., RICE, J. R., CATLIN, A. C., CRABILL, C. L., CHUI, C. C., AND MARKUS, S. 1994. PDELab: An object-oriented framework for building problem solving environments for PDE based applications. In Proceedings of the 2nd Annual Object-Oriented Numerics Conference. Rogue-Wave Software, Corvallis, Oreg., 79-92.
29. WIDROW, B. AND WINTER, R. 1988. Neural nets for adaptive filtering and adaptive pattern recognition. Computer 21, 25-39.
30. ZELL, A., MACHE, N., HUBNER, R., MAMIER, G., VOGT, M., HERRMANN, K.-U., SCHMALZL, M., SOMMER, T., HATZIGEORGIOU, A., DORING, S., AND POSSELT, D. 1993. Stuttgart Neural Network Simulator User Manual. Ver. 3.1. Tech. Rep. 3, Univ. of Stuttgart, Stuttgart, Germany.