Hostname: page-component-8448b6f56d-c47g7 Total loading time: 0 Render date: 2024-04-24T22:00:04.078Z Has data issue: false hasContentIssue false

Information processing and the management of uncertainty

Published online by Cambridge University Press:  07 July 2009

Simon Parsons
Affiliation:
Advanced Computation Laboratory, Imperial Cancer Research Fund, Lincoln's Inn Fields, P.O. Box 123, London WC2A 3PX, UK
Alessandro saffiotti
Affiliation:
IRIDIA, Université Libre de Bruxelles, 50 av. F. Roosevelt, CP 194é6, B-I 050 Bruxelles, Belgium

Extract

The First International Conference on Information Processing and the Management of Uncertainty (IPMU) was held in 1986 at a time of great debate about the necessity of modelling uncertainty in intelligent systems (which at that time largely meant rule-based expert systems) and the best way of doing so. Whereas the founders of the Conference on Uncertainty in Artificial Intelligence (UAI) in the United States set out with the aim of promoting the use of probability, the organisers of IPMU chose a diametrically opposed course. Though there were a few papers on probability at IPMU '86, the main focus was on alternative methods, primarily those based upon fuzzy sets. Though subsequent conferences have seen greater mix of papers, IPMU remains largely non-probabilistic with the result that the bulk of the participants come from Europe rather than the United States (despite the large amount of work on uncertainty, and especially probability, that is carried out in the US) making IPMU something of a counterpoint to UAT. The difference in participation is exacerbated by the location—whilst the UAI remains in North America, IPMU alternates between Paris and other cities in Europe, including Urbino in 1988 and Palma in 1992.

Type
Research Article
Copyright
Copyright © Cambridge University Press 1995

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

References4

Acid, S and deCampos, LM Campos, LM, 1994. “Approximation of causal networks by polytrees: an empirical study”. In: Proc. lPM U, pp 972977.Google Scholar
Anderson, MF, Hudson, DL and Cohen, ME, 1994. “Areas of uncertainty in radiological diagnosis”. In: Proc. IPMU, pp 137141.Google Scholar
Arigoni, O and Rossi, A, 1994. “Uncertainty, fuzzy sets, conceptual sets”. In: Proc. IPMU, pp 12911296.CrossRefGoogle Scholar
Benferhat, S, 1994. “Handling hard rules and default rules in possibilistic logic”. In: Proc. IPMU, pp 11531158.CrossRefGoogle Scholar
Barro, S, Bugarin, A, Félix, P, Ruiz, R, Marin, R and Palacios, F, 1994. “Fuzzy logic applications in cardiology: study of some cases”. In: Proc. IPMU, pp 885891.Google Scholar
Bigham, J, Luo, Z, Cayrac, D, Nordbo, I and Bouyssounouse, B, 1994. “Approaches to integration of uncertain and temporal information in diagnostic reasoning”. In: Proc. IPMU, pp 250255.Google Scholar
Bigham, J, 1994. “Using preference based heuristics to control abductive reasoning”. In: Proc. IPMU, pp 700705.Google Scholar
Binaghi, E, Cirla, ML and Rampini, A, 1994. “A fuzzy logic based system for the quantification of visual inspection in clinical assessment”. In: Proc. IPMU, pp 892897.CrossRefGoogle Scholar
Bosc, P and Pivert, O, 1994. “On the efficiency of the alpha-cut distribution method to evaluate simple fuzzy relational queries”. In: Proc. IPMU, pp 1116.CrossRefGoogle Scholar
Cano, A and Moral, S, 1994. “Heuristic algorithms for the triangulation of graphs”. In: Proc. IPMU, pp 166171.Google Scholar
Cano, A, Cano, J and Moral, S, 1994. “Convex sets of probabilities propagation by simulated annealing”. In: Proc. IPMU, pp 978983.Google Scholar
Cardoso, J, Valette, R and Pradin-Chezalviel, B, 1994. “Linear logic for imprecise firings in object Petri nets”. In: Proc. IPMU, pp 12691274.CrossRefGoogle Scholar
Dawid, AP, Kjærulff, U and Lauritzen, SL, 1994. “Hybrid propagation in junction trees”. In: Proc. IPMU, pp 965971.Google Scholar
deCampos, LM Campos, LM, Huete, JF and Moral, S, 1994. “Uncertainty management using probability intervals”. In: Proc. IPMU, pp 431436.Google Scholar
Dubois, D, Dupinde Saint Cyr, F de Saint Cyr, F and Prade, H, 1994. “Updating, transition constraints and possibilistic Markov chains”. In: Proc. IPMU, pp 826831.Google Scholar
Eklund, PW, Sun, X and Thomas, DA, 1994. “Fuzzy matrices: an application in agriculture”. In: Proc. IPMU, pp 765769.Google Scholar
Esteva, F, Garcia, P and Godo, L, 1994. “On conditioning in similarity logic”. In: Proc. IPMU, pp 9991005.Google Scholar
Ezawa, KJ, 1994. “Evidence propagation on influence diagrams and value of evidence”. In: Proc. IPMU, pp 287292.Google Scholar
Fariāascel Cerro, L cel Cerro, L and Herzig, A, 1994. “Possibility theory and independence”. In: Proc. IPMU, pp 820825.Google Scholar
FerreiroGarcia, R Garcia, R, 1994. “FAM on gain scheduling control of highly nonlinear and disturbed processes”. In: Proc. IPMU, pp 463466.Google Scholar
Gebhardt, J and Kruse, R, 1994. “A numerical framework for possibilistic abduction”. In: Proc. IPMU, pp 809814.Google Scholar
Glorennec, PY and Ambrozy, G, 1994. “Predictive fuzzy control of a heating floor”. In: Proc. IPMU, pp 473477.Google Scholar
Glorennec, PY, Pircher, H and Hespel, JP, 1994. “Fuzzy logic control of blood glucose”. In: Proc. IPMU, pp 916920.Google Scholar
Gottwald, S, 1994. “An approach to handle partially sound rules of inference”. In: Proc. IPMU, pp 706711.Google Scholar
Hajek, P, 1994. “Possibilistic logic as interpretability logic”. In: Proc. IPMU, pp 815819.Google Scholar
Hudson, DL, Cohen, ME and Anderson, MF, 1994. “A hybrid neural network with symbolic action layer for medical decision support”. In: Proc. IPMU, pp 131136.Google Scholar
Jaulent, M-C and Yang, A, 1994. “Application of fuzzy pattern matching to the flexible interrogation of a digital angiographies database”. In: Proc. IPMU, pp 904909.Google Scholar
Jensen, FV and Liang, J, 1994. “dr Hugin: a system for value of information in Bayesian networks”. In: Proc. IPMU, pp 178183.Google Scholar
Kinkielélé, D, and Ayel, M, 1994. “On discovering potential inconsistencies in validating fuzzy knowledge bases”. In: Proc. IPMU, pp 533538.Google Scholar
Kohlas, J and Brachinger, HW, 1994. “Mathematical foundations of evidence theory”. In: Proc. IPMU, pp 5358.Google Scholar
Mellouli, K, 1994. “Decision making using belief functions evaluation of information”. In: Proc. IPMU, pp 4752.Google Scholar
O'Leary, DE, 1994. “Verification and validation of multiple agent systems: combining agent probabilistic judgements”. In: Proc. IPMU, pp 521525.Google Scholar
O'Leary, DE and O'Keefe, R, 1994. “A survey of validation of multiple agent systems”. In: Proc. IPMU, pp 527532.Google Scholar
Olivas, JA and Sobrino, A, 1994. “An application of Zadeh's prototype theory to the prediction of forest fire in a knowledge-based system”. In: Proc. IPMU, pp 747752.Google Scholar
Ozawa, J and Yamada, K, 1994. “Co-operative answering with macro expression of a database”. In: Proc. IPMU, pp 1722.Google Scholar
Paduraru, O, Teodorescu, HN, Costin, M, Ciobanu, A and Gradinaru, S, 1994. “Fuzzy expert system shell for diagnosis and prediction applications”. In: Proc. IPMU, pp 759764.Google Scholar
Parsons, S and Saffiotti, A, 1994. “The qualitative verification of quantitative uncertainty”. In: Proc. IPMU, pp 443448.Google Scholar
Ramparany, F, Lorquet, V and Bouyssounouse, B, 1994. “Combining uncertain and temporal reasoning”. In: Proc. IPMU, pp 256261.Google Scholar
Ribeiro, RA and Baldwin, JF, 1994. “A multiple attribute fuzzy decision support system: two applications”. In: Proc. IPMU, pp 485490.Google Scholar
Ruspini, EH, 1994. “Elastic requirements and similarities: from heuristics to analytical tools”. In: Proc. IPMU.Google Scholar
Sandri, S and Bittencourt, G, 1994. “Possibilistic semantic nets”. In: Proc. IPMU, pp 838843.Google Scholar
Shafer, G, 1994. “Philosophical foundations for causal networks”. In: Proc. IPMU, pp 38.Google Scholar
Shenoy, PP, 1994. “Valuation networks and asymmetric decision problems”. In: Proc. IPMU, pp 153158.Google Scholar
Smits, PC, Mari, M, Teschioni, A, Dellepiani, S and Fontana, F, 1994. “Application of fuzzy methods to segmentation of medical images”. In: Proc. IPMU, pp 910915.Google Scholar
Snow, P, 1994. “Probabilistic models of ignorance and the advent of belief”. In: Proc. IPMU, pp 222227.Google Scholar
vande Stadt, E de Stadt, E and vander Lubbe, JCA der Lubbe, JCA, 1994. “Exploiting independence relations for efficient probability propagation in Bayesian belief networks”. In: Proc. IPMU, pp 172177.Google Scholar
Thiele, H, 1994. “On soft dynamic logic”. In: Proc. IPMU, pp 11591164.Google Scholar
Tsoukiàs, A, 1994. “On using preferences and truth lattices in the definition of new logics”. In: Proc. IPMU, pp 505511.Google Scholar
Valverde, L, 1994. “Fuzzy transitive relations and inference”. In: Proc IPMU.Google Scholar
Virtanen, HE, 1994. “Fuzzy unification”. In: Proc. IPMU, pp 11471152.Google Scholar
Wellman, MP, 1994. “Some varieties of qualitative probability”. In: Proc IPMU, pp 437442.Google Scholar
Wong, SKM, Xiang, Y and Nie, X, 1994. “Representation of Bayesian networks as relational databases”. In: Proc. IPMU, pp 159165.Google Scholar
Xu, H, 1994. “Computing marginals from the marginal representation in Markov trees”. In: Proc. IPMU, pp 275280.Google Scholar