Abstract
Self Adaptive Software monitors its own operation and attempts to correct deviations from required behavior. In the self adaptive architectures we are developing, it accomplishes this by diagnosing the sources of deviant behavior, whether internal program problems, or contextual changes in an embedded program’s environment. The software then responds by reconfiguring itself, to use alternate procedures that either correct the malfunction, or perform better in the current context. We present the GRAVA architecture as an example, and show how it utilizes diagnosis of the external context to limit complexity and enhance robustness in several vision applications.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Baum, L.E.: An inequality and associated maximization technique in statistical estimation for probabilistic functions of a markov process. Inequalities 3, 1–8 (1972)
Ben-Shaul, I., Gazit, H., Holder, O., Lavva, B.: Dynamic self adaptation in distributed systems. In: Robertson, P., Shrobe, H.E., Laddaga, R. (eds.) IWSAS 2000. LNCS, vol. 1936, pp. 134–142. Springer, Heidelberg (2001)
Brooks, R.A.: The intelligent room project. In: Proceedings of the Second International Cognitive Technology Conference (CT 1997), Aizu, Japan (1997)
Charniak, E.: Statistical Language Learning. MIT Press, Cambridge (1993)
Charniak, E.: Statistical techniques for natural language parsing. pp. 33–43 (1997)
Draper, B., Collins, R., Brolio, J., Hansen, A., Riseman, E.: The schema system. Technical Report COINS TR88-76, Computer and Information Science, Univ. Massachusetts at Amherst (1988)
Jackson, J.E.: A user’s guide to Principal Components. John Wiley and Sons, New York (1991)
Jelinek, F., Lafferty, J.D., Mercer, R.L.: Basic methods of probabilistic context-free grammars. In: Laface, P., De Mori, R. (eds.) Speech recognition and understanding. Recent advances, trends, and applications. NATO ASI Series, vol. F75. Springer, Berlin (1992)
Karsai, G., Sztipanovits, J.: A model-based approach to self-adaptive software. IEEE Intelligent Systems 14(3), 46–53 (1999)
Kokar, M.M., Baclawski, K., Eracar, Y.A.: Control theory-based foundations of self-controlling software. IEEE Intelligent Systems 14(3), 37–45 (1999)
Laddaga, R.: Self-adaptive software sol baa 98-12 (1998)
Laddaga, R.: Creating robust software through self-adaptation. IEEE Intelligent Systems 14(3), 26–29 (1999)
Minsky, M.: A framework for representing knowledge. In: Winston, P.H. (ed.) The Psychology of Computer Vision. McGraw-Hill, New York (1975)
Musliner, D.J., Goldman, R.P., Pelican, M.J., Krebsbach, K.D.: Self-adaptive software for hard real-time environments. IEEE Intelligent Systems 14(4), 23–29 (1999)
Nordstrom, G., Sztipanovits, J., Karsai, G., Ledeczi, A.: Metamodeling rapid design and evolution of domainspecific modeling environments. In: Proceedings of the IEEE Conference and Workshop on Engineering of Computer Based Systems (1999)
Oreizy, P., Gorlick, M.M., Taylor, R.N., Heimbigner, D., Johnson, G., Medvidovic, N., Quilici, A., Rosenblum, D.S., Wolf, A.L.: An architecture-based approach to self-adaptive software. IEEE Intelligent Systems 14(3), 54–62 (1999)
Robertson, P.: A corpus based approach to the interpretation of aerial images. In: Proceedings IEE IPA 1999. IEE, Manchester (1999)
Robertson, P.: An architecture for self-adaptation and its application to aerial image understanding. In: Robertson, P., Shrobe, H.E., Laddaga, R. (eds.) IWSAS 2000. LNCS, vol. 1936, pp. 199–223. Springer, Heidelberg (2001)
Robertson, P.: A Self-Adaptive Architecture for Image Understanding. PhD thesis, University of Oxford (2001)
Robertson, P., Brady, J.M.: Adaptive image analysis for aerial surveillance. IEEE Intelligent Systems 14(3), 30–36 (1999)
Robertson, P., Laddaga, R.: Principle component decomposition for automatic context induction. In: Proceedings Artificial and Computational Intelligence 2002, Tokyo, Japan (2002)
Robertson, P., Laddaga, R.: A self-adaptive architecture and its application to robust face identification. In: Ishizuka, M., Sattar, A. (eds.) PRICAI 2002. LNCS (LNAI), vol. 2417, p. 542. Springer, Heidelberg (2002)
Viterbi, A.J.: Error bounds for convolution codes and an asymptotically optimal decoding algorithm. IEEE Transactions on Information Theory 13, 260–269 (1967)
Wallace, C.S.: Classification by minimum-message-length inference. In: Goos, G., Hartmanis, J. (eds.) Advances in Computing and Information–ICCI 1990, pp. 72–81. Springer, Heidelberg (1990)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Robertson, P., Laddaga, R. (2005). Model Based Diagnosis and Contexts in Self Adaptive Software. In: Babaoglu, O., et al. Self-star Properties in Complex Information Systems. SELF-STAR 2004. Lecture Notes in Computer Science, vol 3460. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11428589_8
Download citation
DOI: https://doi.org/10.1007/11428589_8
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-26009-7
Online ISBN: 978-3-540-32013-5
eBook Packages: Computer ScienceComputer Science (R0)