High level learning by imitation consists of learning to emulate high level human cognitive processes. We have been able to solve this problem within a specific setting, searching for a treasure in a maze. The human behaviour can be recorded as time series of observable variables, representing

conditions: no feedback, neutral feedback, and affec-tive feedback. What the students think about the embodied agent and how they feel about the task under the different conditions will be elicited through a questionnaire upon completion of the treasure hunt activity. Moreover, how each condition affects

-based task allocation and Plays for synchronized task execution, to allocate roles amongst robots in the pickup team, and to execute synchronized team actions to accomplish the treasure hunt task.

their technological and managerial competences further. Therefore we can say that Chinese companies particularly value task-related criteria when selecting Western partners. Nevertheless we also find that Chinese companies also include ‘soft ’ factors such trust, compatibility or reputation in their partner selection

Abstract—This paper intends to describe the current status of our group in trying to make a humanoid robot autonomously build an internal representation of an object, and later on to find it in an unknown environment. This problem is named “treasure hunting”. In both cases, the main difficulty

or affective feedback during the treasure hunt. The initial results of the study suggest that the use of the virtual robot increased the perceived difficulty of the instruction-following task, while the affective robot feedback in particular made the questions seem more difficult to answer.

Consider the task of reaching a goal state in a partially or completely unknown domain. To accomplish such a task search algorithms have to explore the domain sufficiently to locate a goal state and a path leading to it, performing therefore what we call uninformed "treasure hunt." Very

in market-based task allocation and plays for synchronized task execution, to allocate roles amongst robots in the pickup team, and to execute synchronized team actions to accomplish the treasure hunt task. I.

brick. Nobody has found one. There might be none. Nevertheless, it is an entertaining sport to go for this treasure hunt for rational cuboids and search- of course with the help of computers. We especially look in this lecture at Soundersons parametrizations and give a short proof of a theorem of Spohn

filter can be used for positioning based on cellular phone measurements, for integrated navigation in aircraft, and for target tracking in aircraft and cars. Finally, the particle filter enables a promising solution to the combined task of navigation and tracking, with possible application to airborne