Éditeur(s) : Springer Heidelberg
Résumé : This study describes how three individual fish, Atlantic cod (Gadus morhua L.), developed a novel behaviour and learnt to use a dorsally attached external tag to activate a self-feeder. This behaviour was repeated up to several hundred times, and over time these fish fine-tuned the behaviour and made a series of goal-directed coordinated movements needed to attach the feeder’s pull string to the tag and stretch the string until the feeder was activated. These observations demonstrate a capacity in cod to develop a novel behaviour utilizing an attached tag as a tool to achieve a goal. This may be seen as one of the very few observed examples of innovation and tool use in fish.
Animal Cognition (1435-9448) (Springer Heidelberg), 2014-05 , Vol. 17 , N. 3 , P. 779-785

Droits : Springer-Verlag Berlin Heidelberg 2013
http://archimer.ifremer.fr/doc/00171/28217/26513.pdf
DOI:10.1007/s10071-013-0710-3
http://archimer.ifremer.fr/doc/00171/28217/

Éditeur(s) : HAL CCSD
Résumé : International audience
This paper focuses on the study of the influence of a newly implemented mechanism on a Pittsburgh-like classifier system. The Adapted Pittsburgh Classifier System is a learning classifier system that uses genetic algorithms to evolve its ruleset. The new mechanism discussed is inspired from Wilson work on the eXtended Classifier System (XCS): it allows the concerned LCS to adapt its rule set when facing a new signal by modifying an existing rule. This mechanism is called covering mechanism due to the fact that the rule is covered up by a new rule which is sensitive to this new signal. Effects of this covering mechanism are first measured on the performances of APCS on well known multi-step environments: maze-type environments (Woods 101 and E2). In addition, further measures presented in this paper indicate that we could possibly rely on the behavior of this covering mechanism to automate the research of a correct cognitive capacity needed by the APCS to solve a given multistep problem.
2008 Eighth International Conference on Hybrid Intelligent Systems
Barcelone, Spain

hal-00520608
https://hal.archives-ouvertes.fr/hal-00520608
DOI : 10.1109/HIS.2008.105

Éditeur(s) : HAL CCSD
Résumé : International audience
This paper demonstrates that a human being using an interface can be efficiently evaluated - in real time - by embedding basic measurements in the interface and using a suitable trained artificial neural network. The approach is introduced through video games but is suitable for any machine capable of valuable measurements on user actions. Of course, the quality of the "diagnostic" depends of the learnability of the task and of the size and quality of the learning base. Typical applications include the detection of fatigue, stress, emotions, the influence of a drug or of medical treatments ; screening a deficit or adequateness to a task, etc. Two successful prototypes are presented, one to predict the mental age of children through a set of simple basic games, and the other to detect if a subject is right-handed of left-handed through a racing car simulation.
Proceeding of the Third International Conferences on Advances in Computer-Human Interactions
St. Maarten, Netherlands Antilles

hal-00601476
https://hal.archives-ouvertes.fr/hal-00601476