Daniel Dubois

How “consciousness” allows a cognitive tutoring agent make good diagnosis during astronauts' training

Striving in the real world is more and more what artificial agents are required to do, and it is not a simple task. Interacting with humans in general, and with students in specific, requires an awful lot of subtlety if one is to be perceived as a great tutor and a pleasant fellow. Similarly, the more various types of information an artificial agent senses, the more apt it may be. But then comes the need to process all this stuff, and that can overwhelm even the most powerful computer. «Consciousness» mechanisms can help and sustain an apt tutor, allowing it to consider various sources of information in diagnosing and guiding learners. We show in the present paper how they effectively support theses processes in the specific context of astronauts training on the manipulation of the Space Station Robotic Manipulation System, Canadarm2.

Automatic Evaluation of Spatial Representations for Complex Robotic Arms Manipulations

This paper describes how a knowledge model allows training software to evaluate spatial cognitive maps and provide tailored assistance.

Decision-Making in Cognitive Tutoring Systems

Human teachers have capabilities that are still not completely uncovered and reproduced into artificial tutoring systems. Researchers have nevertheless developed many ingenious decision mechanisms which obtain valuable results. Some inroads into natural artificial intelligence have even been made, then abandoned for tutoring systems because of the complexity involved and the computational cost. These efforts toward naturalistic systems are noteworthy and still in general use. In this chapter, we describe how some of this AI is put to work in artificial tutoring systems to reach decisions on when and how to intervene. We then take a particular interest in pursuing the path of “natural” AI for tutoring systems, using human cognition as a model for artificial general intelligence. One tutoring agent built over a cognitive architecture, CTS, illustrates this direction. The chapter concludes on a brief look into what might be the future for artificial tutoring systems, biologically-inspired cognitive architectures.