This paper presents a user-driven genetic algorithm for directed graph drawing. An interactive framework is considered where users can focus the algorithm on regions of the drawing that need major improvement, or include domain knowledge as layout constraints. The paper describes how focus and user constraints are managed by the genetic algorithm. The combination of user’s skills with automatic...

This paper presents an algorithm for analyzing social situations within a robot. We contribute a method that allows the robot to use information about the situation to select interactive behaviors. This work is based on interdependence theory, a social psychological theory of interaction and interpersonal situation analysis. Experiments demonstrate the utility of the information provided by the...

Experienced users often have useful knowledge and intuition in solving real-world optimization problems. User can be formulated as inter-variable relationships to assist an algorithm finding good solutions faster. Such interactions also automatically learned from high-performing discovered at intermediate iterations run – a process called innovization. These relations, if vetted by the users, e...