Systems Seminar - ECE

Game Theoretic Tools for Social Cyber-Physical Systems

Lillian RatliffPh.D candidateUniversity of California - Berkeley, Department of EECS

Critical infrastructures are inherently social cyber-physical systems (S-CPS) composed of a complex collection of sensors, controllers, and actuators that work together to improve our daily lives. Within S-CPS there are a number of emerging service models in areas such as building energy management, distributed equipment health monitoring, and the smart grid. These service models require the ability to collect and analyze the copious amounts of data available from sensor webs in S-CPS. In addition, they require a formal understanding of the relationship between the customer and the central planner offering the service, whose interests generally are not aligned. In this talk, I will discuss some game-theoretic tools for S-CPS. In the first part of the talk, I will discuss results on the characterization and computation local Nash equilibria a fundamental equilibrium concept for competing agents. In the second part of the talk, I will focus on energy systems and discuss recent work on the development of a novel bound on the probability of a successful privacy breach by an adversary as well as privacy based contacts in the smart grid.
Lillian Raatliff is a Ph.D. Candidate in Electrical Engineering and Computer Science at UC Berkeley. Her training is in game theory, dynamical systems and control. Her research interests lie at the intersection of the study of non-cooperative games, mechanism design and social cyber-physical systems (S-CPS). She is interested in utilizing the complex datasets captured through new sensing and control technologies being deployed in critical infrastructure, such as the smart grid, to develop data-drive models for both system and agent behavior and then using them in parallel with game theory for analysis and synthesis S-CPS. She is the recipient of a National Science Foundation graduate student fellowship (2009).

Sponsored by

University of Michigan, Department of Electrical Engineering & Computer Science