Towards a Characterisation of Assets and Knowledge Created in Technological Agreements Some Evidence from the Automobile-Robotics Sector

This paper tries to bring new insights on the dynamics of inter-firm by focusing on cognitive and organisational dimensions. We consider the knowledge bases created inside the agreement and the characteristics of such knowledge bases (such as tacitness, level of generality, degree of centralisation...). The nature of assets for supporting this creation is also essential for the redeployability of knowledge created. We began by a brief review of some problems encountered by transactions cost economics and present some case studies of agreements between firms in the automobile and robotics sector. After having presented a taxonomy of knowledge and assets involved in such agreements, we bring some new discussion on the exploration/exploitation's dilemma. We argue finally that our taxonomy may be fruitful for a better understanding of the dynamic of firm boudaries by trying to go deeper into the "black box" of agreements.Inter-firm relations, automobile industry, technological agreements

Information driven self-organization of complex robotic behaviors

Information theory is a powerful tool to express principles to drive autonomous systems because it is domain invariant and allows for an intuitive interpretation. This paper studies the use of the predictive information (PI), also called excess entropy or effective measure complexity, of the sensorimotor process as a driving force to generate behavior. We study nonlinear and nonstationary systems and introduce the time-local predicting information (TiPI) which allows us to derive exact results together with explicit update rules for the parameters of the controller in the dynamical systems framework. In this way the information principle, formulated at the level of behavior, is translated to the dynamics of the synapses. We underpin our results with a number of case studies with high-dimensional robotic systems. We show the spontaneous cooperativity in a complex physical system with decentralized control. Moreover, a jointly controlled humanoid robot develops a high behavioral variety depending on its physics and the environment it is dynamically embedded into. The behavior can be decomposed into a succession of low-dimensional modes that increasingly explore the behavior space. This is a promising way to avoid the curse of dimensionality which hinders learning systems to scale well.Comment: 29 pages, 12 figure

Motion for cooperation and vitality in Human-robot interaction

In social interactions, human movement is a rich source of information for all those who take part in the collaboration. In fact, a variety of intuitive messages are communicated through motion and continuously inform the partners about the future unfolding of the actions. A similar exchange of implicit information could support movement coordination in the context of Human-Robot Interaction. Also the style of an action, i.e. the way it is performed, has a strong influence on interaction between humans. The same gesture has different consequences when it is performed aggressively or kindly, and humans are very sensitive to these subtle differences in others\u2019 behaviors. During the three years of my PhD, I focused on these two aspects of human motion. In a firs study, we investigated how implicit signaling in an interaction with a humanoid robot can lead to emergent coordination in the form of automatic speed adaptation. In particular, we assessed whether different cultures \u2013 specifically Japanese and Italian \u2013 have a different impact on motor resonance and synchronization in HRI. Japanese people show a higher general acceptance toward robots when compared with Western cultures. Since acceptance, or better affiliation, is tightly connected to imitation and mimicry, we hypothesized a higher degree of speed imitation for Japanese participants when compared to Italians. In the experimental studies undertaken both in Japan and Italy,we observed that cultural differences do not impact on the natural predisposition of subjects to adapt to the robot. In a second study, we investigated how to endow a humanoid robot with behaviors expressing different vitality forms, by modulating robot action kinematics and voice. Drawing inspiration from humans, we modified actions and voice commands performed by the robot to convey an aggressive or kind attitude. In a series of experiments we demonstrated that the humanoid was consistently perceived as aggressive or kind. Human behavior changed in response to the different robot attitudes and matched the behavior of iCub, in fact participants were faster when the robot was aggressive and slower when the robot was gentle. The opportunity of humanoid behavior to express vitality enriches the array of nonverbal communication that can be exploited by robots to foster seamless interaction. Such behavior might be crucial in emergency and in authoritative situations in which the robot should instinctively be perceived as assertive and in charge, as in case of police robots or teachers