NS Seminar

Date and Location

Nov 27, 2018 - 3:30pm to 4:30pm
Bldg 434, Room 122


A Dynamic Model of Social Network Formation (presented by Roman Aguilera, Computer Science)

B. Skyrms and R. Pemantle, “A Dynamic Model of Social Network Formation” PNAS 97 (16), 9340-9346 (2000).

We consider a dynamic social network model in which agents play repeated games in pairings determined by a stochastically evolving social network. Individual agents begin to interact at random, with the interactions modeled as games. The game payoffs determine which interactions are reinforced, and the network structure emerges as a consequence of the dynamics of the agents' learning behavior. We study this in a variety of game-theoretic conditions and show that the behavior is complex and sometimes dissimilar to behavior in the absence of structural dynamics. We argue that modeling network structure as dynamic increases realism without rendering the problem of analysis intractable.


Coalitional Game Theory for Cooperative Micro-Grid Distribution Networks (presented by Kevin Smith, Electrical and Computer Engineering)

Saad, W., Han, Z., & Poor, H. V. (2011, June). Coalitional game theory for cooperative micro-grid distribution networks. In Communications Workshops (ICC), 2011 IEEE International Conference on (pp. 1-5). IEEE.

Micro-grid distribution networks that use distributed energy sources are expected to lie at the heart of the emerging smart grid technology. While existing approaches have focused on control and communication aspects in micro-grids, this paper use coalitional game theory to study novel cooperative strategies between the micro-grids of a distribution network. For this purpose, a coalitional game is formulated between a number of micro-grids (e.g., solar panels, wind turbines, PHEVs, etc.) that are, each, servicing a group of consumers (or an area) and that are connected to a macro-grid substation. For forming coalitions, an algorithm is proposed to allow the micro-grids to autonomously cooperate and self-organize into a partition composed of disjoint micro-grid coalitions. Each formed coalition consists of micro-grids that have a surplus of power to transfer or sell and of micro-grids that need to buy or acquire additional power to meet their demand. Within every coalition, the micro-grids coordinate the power transfer among themselves as well as with the macro-grid station, in a way to optimize a utility function that captures the total losses over the distribution power lines. Also, the proposed algorithm allows the micro-grids, in a distributed manner, to self-adapt to environmental changes such as variations in the power needs of the micro-grids. Simulation results show that the proposed algorithm yields a reduction in terms of the average power losses (over the distribution line) per micro-grid, reaching up to 31% improvement relative to the non-cooperative case.