Knowledge mediator Decomposing expert agent knowledge to develop novice agent knowledge comprehension

Abstract

As humans have different levels of expertise, this differentiation becomes one of the obstacles to the construction of knowledge comprehension by exchanging knowledge. To overcome this problem, we decompose experts' knowledge presentation while aiming to build knowledge comprehension in novice agents using concept maps as a knowledge representation of multiplication problems. The proposed collaborative interaction model is a mediator of communication built by CLARION. This collaborative interaction model may be a solution to overcome the problems which arise when building group collaboration systems for learning purposes.