H. Abdi, Les réseaux de neurones. Sciences et technologies de la connaissance, 1994.

A. Agresti, Categorical Data Analysis, 1990.

P. M. Allen and J. M. Mcglade, Dynamics of Discovery and Exploitation: The Case of the Scotian Shelf Groundfish Fisheries, Canadian Journal of Fisheries and Aquatic Sciences, vol.43, issue.6, pp.1187-1200, 1986.
DOI : 10.1139/f86-148

D. R. Anderson, K. P. Burnham, and W. L. Thompson, Null Hypothesis Testing: Problems, Prevalence, and an Alternative, The Journal of Wildlife Management, vol.64, issue.4, pp.912-923, 2000.
DOI : 10.2307/3803199

D. R. Anderson, K. P. Burnham, and G. C. White, AIC Model Selection in Overdispersed Capture-Recapture Data, Ecology, vol.75, issue.6, pp.1760-1793, 1994.
DOI : 10.2307/1939637

S. P. Bannerot, A. , and C. B. , Using frequency distributions of catch per unit effort to measure fish-stock abundance. Transactions of the American Fishery Society, pp.608-617, 1983.

K. P. Burnham, A. , and D. R. , Data-Based Selection of an Appropriate Biological Model: The Key to Modern Data Analysis, Wildlife 2001 Populations, pp.16-30, 1992.
DOI : 10.1007/978-94-011-2868-1_3

H. F. Campbell and A. J. Hand, Modeling the spatial dynamics of the U.S. purse-seine fleet operating in the western Pacific tuna fishery, Canadian Journal of Fisheries and Aquatic Sciences, vol.56, issue.7, pp.1266-1277, 1999.
DOI : 10.1139/f99-009

H. F. Campbell, G. Meyer, and R. B. Nicholl, Search behavior in the purse seine tuna fishery, Natural Resource Modeling, vol.7, pp.15-35, 1993.

D. G. Chen, W. , and D. W. , A neural network model for forecasting fish stock recruitment, Canadian Journal of Fisheries and Aquatic Sciences, vol.56, issue.12, pp.2385-2396, 1999.
DOI : 10.1139/f99-178

L. Dagorn, E. Josse, P. Bach, and A. Bertrand, Mod??lisation du comportement des thons autour des objets flottants??: des individus aux agr??gations., Aquatic Living Resources, vol.13, issue.4, pp.203-211, 2000.
DOI : 10.1016/S0990-7440(00)01065-2

M. W. Dorn, ), Canadian Journal of Fisheries and Aquatic Sciences, vol.55, issue.1, pp.180-198, 1998.
DOI : 10.1139/f97-234

M. W. Dorn, Fishing behavior of factory trawlers: a hierarchical model of information processing and decision-making, ICES Journal of Marine Science, vol.58, issue.1, pp.238-252, 2001.
DOI : 10.1006/jmsc.2000.1006

M. Dreyfus-leon, Individual-based modelling of fishermen search behaviour with neural networks and reinforcement learning, Ecological Modelling, vol.129, pp.287-297, 1999.

M. Dreyfus-leon and D. Gaertner, Fleet dynamics and information exchange simulation modeling with artificial neural network. In "From Animals to Animats 7, Proceedings of the 7th International Conference on Simulation of Adaptive Behavior, ISAB, pp.397-398, 2002.

A. Fonteneau, D. Gaertner, and V. Nordstrom, An overview of problems in the catch per unit of effort and abundance relationship for the tropical purse seine fisheries. Collective Volume of Scientific Papers, ICCAT, issue.3, pp.49-258, 1999.

D. Gaertner, M. Pagavino, and J. Marcano, Influence of fisher's behaviour on the catchability of surface tuna schools in the Venezuelan purse-seiner fishery in the Caribbean Sea, Canadian Journal of Fisheries and Aquatic Sciences, vol.56, pp.394-406, 1999.

J. B. Gatewood, cooperation, competition, and synergy: information-sharing groups among Southeast Alaskan salmon seiners, American Ethnologist, vol.57, issue.2, pp.350-370, 1984.
DOI : 10.1525/ae.1984.11.2.02a00080

D. M. Gillis and R. M. Peterman, Implications of interference among fishing vessels and the ideal free distribution to the interpretation of CPUE, Canadian Journal of Fisheries and Aquatic Sciences, vol.55, issue.1, pp.37-46, 1998.
DOI : 10.1139/f97-206

V. Grimm, T. Wyszomirski, D. Aikman, and J. Uchmanski, Individual-based modelling and ecological theory: synthesis of a workshop, Ecological Modelling, vol.115, issue.2-3, pp.275-282, 1999.
DOI : 10.1016/S0304-3800(98)00186-0

J. A. Gulland, Catch per unit effort as a measure of abundance. Rapports et Procès-verbaux des Réunions Conseil International pour l'Exploitation de la Mer, pp.8-14, 1964.

S. J. Harley, R. A. Myers, and A. Dunn, Is catch-per-unit-effort proportional to abundance?, Canadian Journal of Fisheries and Aquatic Sciences, vol.58, issue.9, pp.1760-1772, 2001.
DOI : 10.1139/f01-112

R. Hilborn and M. Mangel, The ecological detective Confronting models with data, In Monographs in Population Biology, vol.28, pp.131-179, 1997.

R. Hilborn and C. J. Walters, A General Model for Simulation of Stock and Fleet Dynamics in Spatially Heterogeneous Fisheries, Canadian Journal of Fisheries and Aquatic Sciences, vol.44, issue.7, pp.1366-1369, 1987.
DOI : 10.1139/f87-163

R. Hilborn and C. J. Walters, Quantitative Fisheries Stock Assessment. Choice, Dynamics and Uncertainty, 1992.
DOI : 10.1007/978-1-4615-3598-0

D. S. Holland and J. G. Sutinen, An empirical model of fleet dynamics in New England trawl fisheries, Canadian Journal of Fisheries and Aquatic Sciences, vol.56, issue.2, pp.253-264, 1999.
DOI : 10.1139/f98-169

A. Laurec, L. Guen, and J. , CPUE des senneurs et abondance: impact des structures fines. Collective Volume of Scientific Papers, ICCAT, vol.7, issue.1, pp.30-54, 1977.

J. Lebreton, K. P. Burnham, J. Clobert, A. , and D. R. , Modeling Survival and Testing Biological Hypotheses Using Marked Animals: A Unified Approach with Case Studies, Ecological Monographs, vol.62, issue.1, pp.67-118, 1992.
DOI : 10.2307/2937171

S. Lek, M. Delacoste, P. Baran, I. Dimopoulos, J. Lauga et al., Application of neural networks to modelling nonlinear relationships in ecology, Ecological Modelling, vol.90, issue.1, pp.39-52, 1996.
DOI : 10.1016/0304-3800(95)00142-5

M. Mangel, C. , and C. W. , Uncertainty, search, and information in fisheries, Journal du Conseil International pour l'Exploration de la Mer, pp.93-103, 1983.
DOI : 10.1093/icesjms/41.1.93

L. Millischer, Modélisation individu centrée des comportements de recherche des navires de pêche Approche générique spatialement explicite par systèmes multi-agents. Intérêts pour l'analyse des stratégies et des puissances de pêche. Doctoral thésis, 2000.

N. Oreskes, K. Shrader-frechette, and K. Belitz, Verification, Validation, and Confirmation of Numerical Models in the Earth Sciences, Science, vol.263, issue.5147, pp.641-646, 1994.
DOI : 10.1126/science.263.5147.641

J. E. Paloheimo, D. , and L. M. , Abundance and fishing success, Rapports et Procès-verbaux des Réunions du Conseil International pour Exploration de la Mer, pp.152-163, 1964.

R. M. Peterman and G. J. Steer, Relation Between Sport-Fishing Catchability Coefficients and Salmon Abundance, Transactions of the American Fisheries Society, vol.110, issue.5, pp.585-593, 1981.
DOI : 10.1577/1548-8659(1981)110<585:RBSCCA>2.0.CO;2

URL : http://doi.org/10.1577/1548-8659(1981)110<585:rbscca>2.0.co;2

B. J. Pyper and R. M. Peterman, Comparison of methods to account for autocorrelation in correlation analyses of fish data, Canadian Journal of Fisheries and Aquatic Sciences, vol.55, issue.9, pp.2127-2140, 1998.
DOI : 10.1139/f98-104

L. J. Richards and J. T. Schnute, An Experimental and Statistical Approach to the Question: Is CPUE an Index of Abundance?, Canadian Journal of Fisheries and Aquatic Sciences, vol.43, issue.6, pp.1214-1227, 1986.
DOI : 10.1139/f86-151

D. E. Rumelhart, G. E. Hinton, W. , and R. J. , Learning representations by back-propagating errors, Nature, vol.85, issue.6088, pp.533-536, 1986.
DOI : 10.1038/323533a0

G. A. Rose and D. W. Kulka, ) declined, Canadian Journal of Fisheries and Aquatic Sciences, vol.56, issue.S1, pp.56-118, 1999.
DOI : 10.1139/f99-207

S. B. Saila, Guide to some computerized artificial intelligence methods, Computers in Fisheries Research, pp.8-40, 1996.
DOI : 10.1007/978-94-015-8598-9_2

B. Warner and M. Misra, Understanding neural networks as statistical tools. The American Statistician, pp.284-293, 1996.
DOI : 10.1080/00031305.1996.10473554

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.51.6595

J. A. Wilson, Fishing for Knowledge, Land Economics, vol.66, issue.1, pp.12-29, 1990.
DOI : 10.2307/3146679