Abstract
Normal proof procedures in abductive logic programming assume that a given program does not change until the proof is completed. However, while a proof is being constructed, new knowledge which affects the proof might be acquired. This paper addresses two important issues: 1. How is it confirmed that the proof being constructed is not affected by the addition of a clause? 2. If affected, how are the invalid parts of the proof restored? The abductive proof procedure used in this paper is Kakas and Mancarella's procedure and is extended to prepare for proof checking and proof restoration. It is shown that any invalid part of a proof can be restored if some additional goals are solved. These additional goals can be added before a proof is completed.
Preview
Unable to display preview. Download preview PDF.
References
J. deKleer. An assumption-based TMS. Artificial Intelligence, 28:127–162, 1986.
J. Doyle. A truth maintenance system. Artificial Intelligence, 12:231–272, 1979.
P. M. Dung. An abductive foundation for non-monotonic truth maintenance. In World Conference on Fundamentals of Artificial Intelligence, 1991.
E. Eshghi and R. A. Kowalski. Abduction compared with negation by failure. In International Conference on Logic Programming, pages 234–254, 1989.
K. Eshghi. Abductive planning with event calculus. In International Conference and Symposium on Logic Programming, pages 562–579, 1988.
L. Giordano and A. Martelli. Generalized stable models, truth maintenance and conflict resolution. In International Conference on Logic Programming, pages 421–441, 1990.
H. Hayashi. Abductive proofs in dynamic databases. Technical Report 744, Department of Computer Science, Queen Mary and Westfield College, University of London, 1997.
K. Inoue. An abductive procedure for the CMS/ATMS. In ECAI90 International Workshop on Truth Maintenance, 1990.
U. Junker. A correct non-monotonic ATMS. In International Joint Conference on Artificial Intelligence, pages 1049–1054, 1989.
A. C. Kakas, R. A. Kowalski, and F. Toni. The role of abduction in logic programming. Handbook of Logic in Artificial Intelligence and Logic Programming, 5, 1997.
A. C. Kakas and P. Mancarella. Database updates through abduction. In International Conference on Very Large Databases, pages 650–661, 1990.
A. C. Kakas and P. Mancarella. On the relation between truth maintenance and abduction. In Pacific Rim International Conference on Artificial Intelligence, pages 438–443, 1990.
R. Kowalski. Using meta-logic to reconcile reactive with rational agents. In Meta-Logic and Logic Programming, pages 227–242, 1995.
R. Kowalski and F. Sadri. Towards a unified agent architecture that combines rationality with reactivity. Department of Computer Science, Imperial College, University of London, 1996.
R. A. Kowalski and F. Sadri. An agent architecture that unifies rationality with reactivity. Department of Computer Science, Imperial College, University of London, 1997.
L. R. Missiaen, M. Denecker, and M. Bruynooghe. CHICA, an abductive planning system based on event calculus. Journal of Logic and Computation, 5(5):579–602, 1995.
J. A. Dávila Quintero. Agents in logic programming. PhD thesis, Department of Computer Science, Imperial College, University of London, 1997.
R. Reiter and J. deKleer. Foundations of assumption-based truth maintenance systems: preliminary report. In AAAI87, pages 183–188, 1987.
W. L. Rodi and S. G. Pimentel. A non-monotonic ATMS using stable bases. In International Conference on Principles of Knowledge Representation and Reasoning, pages 485–495, 1991.
S. Russell and P. Norvig. Artificial Intelligence: A Modern Approach. Prentice Hall, 1995.
K. Satoh and N. Iwayama. Computing abduction using the TMS. In International Conference on Logic Programming, pages 505–518, 1990.
M. Shanahan. Exploiting dependencies in search and inference mechanisms. PhD thesis, King's College, University of Cambridge, 1987.
M. Shanahan. An incremental theorem prover. In International Joint Conference on Artificial Intelligence, pages 987–989, 1987.
M. Shanahan. Event calculus planning revisited. In European Conference on Planning, pages 390–402, 1997.
M. Shanahan. Reinventing shakey. In Working Notes of the AAAI Fall Symposium on Cognitive Robotics, to appear.
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 1998 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Hayashi, H. (1998). Knowledge assimilation and proof restoration through the addition of goals. In: Giunchiglia, F. (eds) Artificial Intelligence: Methodology, Systems, and Applications. AIMSA 1998. Lecture Notes in Computer Science, vol 1480. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0057453
Download citation
DOI: https://doi.org/10.1007/BFb0057453
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-64993-9
Online ISBN: 978-3-540-49793-6
eBook Packages: Springer Book Archive