Social Robot Intelligence and Network Consensus

Synthetic intelligence models are highly relevant to the fast growing field of social robotics. Robots interacting with humans in the context of a non-lab environment are being upgraded at a fast pace in order to meet social expectations. To foster the integration in human societies, and hence coping with expectations, robots are likely to be endowed with typically human attributes, such as synthetic personality. Such social personality is the result of the interaction of a number of systems, some of high complexity, and can be thought of as a network of dynamic systems. The paper addresses the relations between frameworks consistent with synthetic intelligence models from Psychology, and models of networks with nonsmooth dynamics and consensus problems. The goals are (i) to achieve a framework that can establish bridges between architectures including concepts from social sciences and concepts from nonsmooth dynamic systems, and (ii) to determine the basic properties for such framework. Basic continuity and convexity properties are shown to be at the core of the framework.

[1]  G. Smirnov.  Introduction to the Theory of Differential Inclusions , 2002 .

[2]  Akira Namatame,et al.  Agent-based modeling and network dynamics , 2016 .

[3]  María Malfaz,et al.  Multimodal Human-Robot Interaction Framework for a Personal Robot , 2006, ROMAN 2006 - The 15th IEEE International Symposium on Robot and Human Interactive Communication.

[4]  Josef Hofbauer,et al.  Stochastic Approximations and Differential Inclusions , 2005, SIAM J. Control. Optim..

[5]  Mason A. Porter,et al.  Dynamical Systems on Networks: A Tutorial , 2014, ArXiv.

[6]  E.M. Atkins,et al.  A survey of consensus problems in multi-agent coordination , 2005, Proceedings of the 2005, American Control Conference, 2005..

[7]  Matthias Scheutz,et al.  The Architectural Basis of Affective States and Processes , 2005, Who Needs Emotions?.

[8]  N. Wouw,et al.  Stability and Convergence of Mechanical Systems with Unilateral Constraints , 2008 .

[9]  I. Kant.  Anthropology from a pragmatic point of view , 1974 .

[10]  Jan Lunze,et al.  What Is a Hybrid System , 2002 .

[11]  Chai Wah Wu,et al.  Control of Networks of Coupled Dynamical Systems , 2013 .

[12]  Frank L. Lewis,et al.  Manufacturing Systems Control Design: A Matrix-based Approach (Advances in Industrial Control) , 2006 .

[13]  Johan Karlsson,et al.  Reliability Analysis of Consensus in Cooperative Transport Systems , 2013, ASCoMS@SAFECOMP.

[14]  G. Borges,et al.  Robust stability of networked control systems , 2009, 2009 IEEE International Conference on Control and Automation.

[15]  Chai Wah Wu,et al.  On control of networks of dynamical systems , 2010, Proceedings of 2010 IEEE International Symposium on Circuits and Systems.

[16]  Guangming Xie,et al.  Necessary and sufficient conditions for solving consensus problems of double‐integrator dynamics via sampled control , 2010 .

[17]  Takayuki Kanda,et al.  Human-Robot Interaction in Social Robotics , 2012 .

[18]  R. E. Christal,et al.  Recurrent personality factors based on trait ratings. , 1992, Journal of personality.

[19]  Rafal Goebel,et al.  Solutions to hybrid inclusions via set and graphical convergence with stability theory applications , 2006, Autom..

[20]  Huimin Lu,et al.  Brain Intelligence: Go beyond Artificial Intelligence , 2017, Mobile Networks and Applications.

[21]  Takeshi Taniguchi,et al.  Global existence of solutions of differential inclusions , 1992 .

[22]  Reza Olfati-Saber,et al.  Consensus and Cooperation in Networked Multi-Agent Systems , 2007, Proceedings of the IEEE.

[23]  Richard M. Feldman,et al.  Manufacturing Systems Modeling and Analysis , 2008 .

[24]  Denis V. Efimov,et al.  Robustness of homogeneous and locally homogeneous differential inclusions , 2014, 2014 European Control Conference (ECC).

[25]  R. Cattell.  The scientific analysis of personality , 1970 .

[26]  K. Hiraishi,et al.  Design of networked control systems using a stochastic switching systems approach , 2012, IECON 2012 - 38th Annual Conference on IEEE Industrial Electronics Society.

[27]  Wei Zhang,et al.  Stability of networked control systems: explicit analysis of delay , 2000, Proceedings of the 2000 American Control Conference. ACC (IEEE Cat. No.00CH36334).

[28]  Eduardo Sontag.  Input to State Stability: Basic Concepts and Results , 2008 .

[29]  E. P. Ryan,et al.  Feedback controlled differential inclusions and stabilization of uncertain dynamical systems , 1988 .

[30]  Richard M. Murray,et al.  Information flow and cooperative control of vehicle formations , 2004, IEEE Transactions on Automatic Control.

[31]  João Sequeira.  Dependability in robotics as a consensus problem , 2017, 2017 IEEE International Conference on Robotics and Biomimetics (ROBIO).

[32]  Shuichiro Yamamoto,et al.  A Framework for Dependability Consensus Building and In-Operation Assurance , 2013, J. Wirel. Mob. Networks Ubiquitous Comput. Dependable Appl..