Human Discovery and Machine Learning

Christopher Dartnell, Éric Martin, Hélène Hagège, Jean Sallantin
2008 International Journal of Cognitive Informatics and Natural Intelligence  
Submission to IJCINI This paper studies machine learning paradigms from the point of view of human cognition. Indeed, conceptions in both mahine learning and human learning evolved from a passive to an active conception of learning. Our objective is to provide an interaction protocol suited to both humans and machines, to enable assisting human discoveries by learning machines. We identify the limitations of common machine learning paradigms in the context of scientific discovery, and we
more » ... very, and we propose an extension inspired by game theory and multi-agent systems. We present individual cognitive aspects of this protocol as well as social considerations, and we relate encouraging results concerning a game implementing it.
doi:10.4018/jcini.2008100105 fatcat:hovx5z7vv5f3jfnsdffwwmwntu