( about . research . teaching . outreach . personal ) ( ratliffl at eecs.berkeley )

Generally, I am interested in game theory and dynamical systems. In particular, I am examining ways in which games can be decomposed from a structural point of view. It is common in many engineering problems for strategy spaces or player cost functions to be non-convex. In addition, agents may be myopic. These observations motivate the need for a characterization of equilibrium concepts in games that is amenable to computation. My research explores these concepts from a dynamical systems perspective. I am also interested in applying other tools from economics to engineering problems, such as mechanism design and pricing, for the purpose of behavior modification in games arising in engineering applications such as cyber-physical systems.

Differential topology and game theory:

The aim of this project is to utilize tools from differential topology and geometry to study the interaction of competitive agents. In particular, by looking at games in which the strategy spaces are non-convex, we may develop useful decompositions in order to study existence of equilibria and their properties in this more abstract setting. Further, we have developed a characterization of local Nash equilibria that is computable. We term these equilibria differential Nash equilibria. The goal is to use the analytical and computational advancements to developing novel schemes for decentralized control in engineered systems as well as on–line identification techniques for human agents. (Collaborator: Samuel Burden)

Pricing for coordination of noncooperative agents:

The goal of this project is to design pricing mechanisms to coordinate non-cooperative agents. Applications that are considered include efficient energy management in buildings, controlled diffusion in multi-agent networks, and network security. In a non-cooperative game theoretic framework, the goal is to design pricing schemes to close the gap between the decentralized and the centralized cost. In addition, we are interested in designing robust pricing mechanisms. In an effort to do so, we first characterize when feedback Nash strategies are stable and use this characterization to inform the design of pricing mechanisms. (Collaborators: Sam Coogan, Daniel Calderone)

Utility learning in games:

It is often that case that one desires to compute an equilibrium given the utility functions of selfish agents. We pose the inverse question. That is we are interested in learning, from observations of the outcome of a series of games, the utility functions of the participating agents. Given a correlated equilibrium of a game and observations of the players actions, we solve the inverse problem of determining the utility function of each of the agents by parameterizing their utility functions and learning the weights. The tools that we have developed thus far are for finite games. We are investigating methods to extend the results to infinite games. (Collaborators: Aaron Bestick)

Disaggregation:

Disaggregation is the process of taking an aggregated signal and decomposing it into its components. The application we are interested in is energy disaggregation where the aggregate signal is the power consumption for a whole building (residential or commercial) and the goal is to decompose the aggregate signal into the power signal for all the contributing devices. By providing the disaggregated data to consumers, we are enabling them to construct methods for energy efficient operation of the building. Disaggregation of consumer energy data evokes privacy concerns. There is an inherent trade-off between privacy and disaggregation. Our goal is to develop disaggregation algorithms that provide useful information to consumers while preserving some degree of privacy. (Collaborators: Aaron Bestick, Henrik Ohlsson, Roy Dong)

In Preparation

Lillian J. Ratliff, Samuel Coogan, Daniel Calderone, S. Shankar Sastry. "Pricing for Coordination in Linear-Quadratic Dynamic Games." 2013.

Lillian J. Ratliff, Samuel A. Burden, S. Shankar Sastry. "On the Characterization and Computation of Local Nash equilibria." 2013.

Papers

Lillian J. Ratliff, Samuel A. Burden, Shankar Sastry. "Genericity and Structural Stability of Non--degenerate Differential Nash Equilibria." 2013. Submitted.

Lillian J. Ratliff, Samuel A. Burden, Shankar Sastry. "Characterization and Computation of Local Nash Equilibria in Continuous Games." 51st Annual Allerton Conference on Communication, Control, and Computing, 2013. To Appear. (PDF)

Roy Dong, Lillian Ratliff, Henrik Ohlsson, Shankar Sastry. "Energy Disaggregation via Adaptive Filtering." 51st Annual Allerton Conference on Communication, Control, and Computing, 2013. To Appear. (arXiv)

Roy Dong, Lillian Ratliff, Henrik Ohlsson, Shankar Sastry. "A Dynamical Systems Approach to Energy Disaggregation." IEEE Conference on Decision and Control, 2013. To Appear. (arXiv)

Daniel Calderone, Lillian J. Ratliff, S. Shankar Sastry. "Pricing Design for Robustness in Linear-Quadratic Dynamic Games." IEEE Conference on Decision and Control, 2013. To Appear.

Aaron Bestick, Lillian Ratliff, Po Yan, Ruzena Bajcsy, S. Shankar Sastry. "An Inverse Correlated Equilibrium Framework for Utility Learning in Multiplayer, Noncooperative Settings." Conference on High Confidence Networked Systems, 2013. DOI: 10.1145/2461446.2461449 (PDF)

Samuel Coogan, Lillian Ratliff, Daniel Calderone, Claire Tomlin, S. Shankar Sastry. "Energy Management via Pricing in LQ Dynamic Games." American Control Conference, 2013. (PDF)

Lillian Ratliff, Samuel Coogan, Daniel Calderone, S. Shankar Sastry. " Pricing in Linear-Quadratic Dynamic Games." in 50th Annual Allerton Conference on Communication, Control, and Computing, 2012. DOI: 10.1109/Allerton.2012.6483440 (PDF)

Lillian Ratliff and Pushkin Kachroo. "Validating numerically consistent macroscopic traffic models using microscopic data," in Transportation Research Board 89th Annual Meeting, 2010.

Daniel P. Cook, Yitung Chen, Lillian J. Ratliff, Huajun Chen, and Jian Ma. "Numerical Modeling of EM Pump Efficiency" in ASME Conference Proceedings, 2006.

Tech Reports

Henrik Ohlsson, Lillian Ratliff, Roy Dong, Shankar Sastry. "Blind Identification of ARX Models with Piecewise Constant Inputs." arXiv:1303.6719, 2013. (PDF)

Posters

Lillian Ratliff, Daniel Calderone, Samuel Coogan, S. Shankar Sastry. "Pricing for Coordination in Dynamic Games." at FORCES Kickoff Meeting, Washington, D.C. April, 2013. (PDF)

Daniel Calderone, Samuel Coogan, Lillian Ratliff, Anil Aswani, Claire Tomlin, S. Shankar Sastry. "Quadratic incentive design for noncooperative distributed control" Conference on High Confidence Networked Systems (HiCoNS) at CPS Week 2012, Beijing, China, May 2012. (PDF)

Presentations

Daniel Calderone, Samuel Coogan, Lillian Ratliff, Anil Aswani, Claire Tomlin, S. Shankar Sastry. "Quadratic incentive design for noncooperative distributed control" Conference on High Confidence Networked Systems (HiCoNS) at CPS Week 2012, Beijing, China, May 2012. (As work in Progress)

MS thesis topic: Uncertainty Propagation in Dynamical Systems.

Advisor: Pushkin Kachroo