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SUMMARY:Vortrag von Prof. John S. Baras
DESCRIPTION:  \nProf. John S. Baras\nDepartment of Electrical and Computer Engineering\nInstitute for Systems Research University of Maryland College Park, USA  \nTuesday 2015-06-16 16:00\n IST-Seminar-Room V2.268 - Pfaffenwaldring 9 - Campus Stuttgart-Vaihingen  \nAbstract\nWe consider collaborative decision making and control in multi-agent systems.\nLearning is an important ingredient in such systems. The emphasis is to derive as simple as\npossible distributed algorithms that work provably very well, while having minimal knowledge of the\nsystem and its parameters; thus the need for distributed learning. Agents’ understanding of others’\nbehaviors is shaped through observing their actions over a long time. In order to maximize their\npay-off, they need to learn the others’ behavior and coordinate with them. We consider a behavior\nlearning algorithm for a class of behavior functions and study its effects on the emergence of\ncoordination in the network. The conditions under which the learning algorithm converges are\nstudied. Next we consider multi-agent systems, with each agent picking actions from a finite set\nand receiving a payoff depending on the actions of all agents. The exact form of the payoffs is\nunknown and only their values can be measured by the respective agents. We develop a decentralized\nalgorithm that leads to the agents picking welfare optimizing actions utilizing the interactions in\nthe payoffs from the agents’ actions, and if needed very simple bit-valued information exchanges\nbetween the agents over a directed communication graph. Conditions that guarantee convergence to\nwelfare minimizing actions w.p. 1 are derived. We next consider the continuous time and continuous\nstate space version of the problem based on ideas from extremum seeking control. We show\nconvergence of the proposed algorithm to an arbitrarily small neighborhood of a local minimizer of\nthe welfare function. Our results show how indirect communications(signaling between the agents via\ntheir interactions through the system) and direct communications (direct messages sent between\ntheagents) can complement each other and lead to simple distributed control algorithms with\nremarkably good performance. Several applications are briefly discussed. We close by describing\ncurrent and future research directions.\nBiographical Information\nDiploma in Electrical and Mechanical Engineering from the National Technical\nUniversity of Athens, Greece, 1970; M.S., Ph.D. in Applied Mathematics from Harvard University\n1971, 1973. Since 1973, faculty member in the Electrical and Computer Engineering Department, and\nin the Applied Mathematics, Statistics and Scientific Computation Program, at the University of\nMaryland College Park. Since 2000, faculty member in the Fischell Department of Bioengineering.\nSince 2014, faculty member in the Mechanical Engineering Department. Founding Director of the\nInstitute for Systems Research (ISR), 1985 to 1991. Since 1991, Founding Director of the Maryland\nCenter for Hybrid Networks (HYNET). Since 2013, Guest Professor at the Royal Institute of\nTechnology (KTH), Sweden. IEEE Life Fellow, SIAM Fellow, AAAS Fellow, and a Foreign Member of the\nRoyal Swedish Academy of Engineering Sciences (IVA). Received the 1980 George Axelby Prize from the\nIEEE Control Systems Society, the 2006 Leonard Abraham Prize from the IEEE Communications Society,\nthe 2014 Tage Erlander Guest Professorship from the Swedish Research Council, and a three year\n(2014-2017) Senior Hans Fischer Fellowship from the Institute for Advanced Study of the Technical\nUniversity of Munich, Germany. Professor Baras' research interests include automatic control\ncommunication and computing systems and networks, and model-based systems engineering.
DTSTART;VALUE=DATE:20150616
URL;VALUE=URI:https://www.ist.uni-stuttgart.de/de/veranstaltungen/Vortrag-von-Prof.-John-S.-Baras/
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