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SUMMARY:Collaborating Swarms\, Multi-network Topologies and  Constrained C
 oalitional Games - Professor John Baras (University of Maryland)
DTSTART:20100325T140000Z
DTEND:20100325T150000Z
UID:TALK23733@talks.cam.ac.uk
CONTACT:Dr Ioannis Lestas
DESCRIPTION:We consider the problem of autonomous collaboration in groups 
 of robots or vehicles or agents in general. We describe methods for derivi
 ng local coordination rules using techniques from time-varying Markov rand
 om fields\, which result in distributed asynchronous coordination algorith
 ms using parallel Gibbs samplers. The algorithms circumvent the well known
  problem of traditional potential methods that get stuck in locally optima
 l paths. We show that under reasonable and mild assumptions globally optim
 al coordination paths emerge from these local strategies. We then consider
  the tradeoffs between performance and execution time. We develop and anal
 yze two additional distributed coordination algorithms to speed up converg
 ence\, a hybrid one which is a mixture between deterministic gradient coor
 dination and randomized Gibbs samplers\, and another one which adds memory
  to this second hybrid algorithm. We demonstrate that these algorithms con
 verge much faster while still resulting in nearly optimal paths. We then i
 nvestigate the role of the communication topology among the collaborating 
 agents in improving performance of distributed algorithms on graphs\, such
  as convergence speed. We rigorously demonstrate that Small World graphs e
 merge as a good tradeoff between performance and efficiency in consensus p
 roblems\, where the latter serves as a prototypical coordination problem. 
 We discuss extensions to expander graphs and the significance of separatin
 g the collaboration topology from the communication topology in collaborat
 ing swarms. Next we introduce constrained coalitional games and we show th
 at they capture in a fundamental way the basic tradeoff of benefits vs. co
 st of collaboration\, in networked collaborating systems. We demonstrate t
 hat various simple models of constrained coalitional games can explain net
 work formation and the emergence or not of collaboration. We close with co
 nclusions on autonomic networked swarms and examples from biology\, engine
 ering\, social and economic networks\, and provide a brief list of interes
 ting future research directions. 
LOCATION:Cambridge University Engineering Department\, LR5
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