( about . research . teaching . outreach . personal . calendar )

Lillian J. Ratliff

ratliffl at eecs.berkeley

Ph.D. student, EECS at UC Berkeley

( current research . publications . past research )


(NEW***) Link to CDC 2014 Workshp: Big Data Analytics for Societal Scale Cyber-Physical Systems: Energy Systems

Current Research

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My research interests lie at the intersection of non-cooperative games, incentive design, statistical learning, and societal scale cyber-physical systems. We now collect very large and complex data sets through new sensing and control technologies that are currently being deployed in critical infrastructure such as healthcare and transportation systems as well as the smart grid. I am interested in developing data-driven models for agent behavior in social cyber-physical systems and utilizing these models to design incentives for behavior modification. Incentives give rise to new vulnerabilities such as privacy and security issues. Currently I am working on designing privacy-preserving and resilient incentive strategies.

Differential topology and game theory: (show/hide)

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 [UC Berkeley])

Incentive design and utility learning in games: (show/hide)

We model the interaction between non--cooperative agents and a social planner as a reversed Stackelberg game where the social planner is the leader and the agents are the followers that play simultaneously. The social planner would like to modify the agents' behavior so that it aligns with some desired behavior which allows the social planner to meet her objective. However, we assume that the social planner does not know the agents' utility functions and hence must learn them in order to design incentives which modify the agents behavior.

Through a social game we integrate building occupants into the control and management of an office building that is instrumented with networked embedded systems for sensing and actuation. The goal of the social game is to both incentivize building occupants to be more energy efficient and learn behavioral models for occupants so that the building can be made resilient and sustainable through automation. The social game for energy savings that we have designed is such that occupants in an office building vote according to their usage preferences of shared resources and are rewarded with points based on how energy efficient their strategy is in comparison with the other occupants. Having points increases the likelihood of the occupant winning in a lottery. (Collaborators: Ming Jin [UC Berkeley], Ioannis Konstantakopoulos [UC Berkeley], Costas Spanos [UC Berkeley])

Pricing for coordination of noncooperative agents: (show/hide)

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 [UC Berkeley], Daniel Calderone [UC Berkeley])

Disaggregation/Non-intrusive Load Monitoring: (show/hide)

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. In addition, we are developing techniques for behavior modification using tools from game theory and mechanism design. The mechanisms we seek are to some degree privacy preserving. (Collaborators: Aaron Bestick [UC Berkeley], Henrik Ohlsson [C3 Energy, UC Berkeley], Roy Dong [UC Berkeley])

Privacy and Insurance Contracts: (show/hide)
By examining the fundamental limits of non-intrusive load monitoring, we developed a privacy metric. We use this privacy metric for designing privacy-based service contracts to consumers in which privacy is viewed as a good and electricity service is offered as a product line differentiated according to privacy where consumers can self-select the level of privacy that fits their needs and wallet. (Collaborators: Henrik Ohlsson[C3 Energy, UC Berkeley], Roy Dong, Carlos Barreto [UT Dallas], Alvaro A. Cárdenas [UT Dallas])

Recent Talks

(planned) CDC, LA, Dec. 2014, Organizing and speaking at workshop on 'Big Data Analytics for Societal Scale Cyber-Physical Systems: Energy Systems'

Allerton, IL, Oct. 2014, Social Game for Building Energy Efficiency: Incentive Design.

IFAC, Cape Town, South Africa, August 2014, Incentive Design and Utility Learning via Energy Disaggregation.

ACC, Portland Oregon, 06 June 2014, Genericty and Structural Stability of Non-degenerate Differential Nash Equilibria

Stanford, 30 May 2014, Game Theoretic Tools for Societal Scale Cyber-Physical Systems

PDE Seminar, Math Department Berkeley, 09 May 2014, Convexity in Multidimensional Screening

PDE Seminar, Math Department Berkeley, 25 April 2014, Multidimensional Screening

EECS Seminar, University of Michigan, 25 March 2014, Game Theoretic Tools for Societal Scale CPS

Publications, &c.

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In Preparation

Lillian J. Ratliff, Pushkin Kachroo, and S. Shankar Sastry. "Observability and Resilience in Networked Transportation Systems." 2014.

Lillian J. Ratliff, Daniel Calderone, Samuel Coogan, S. Shankar Sastry. "Pricing for Coordination in Dynamic Games." 2014.

Lillian J. Ratliff, Samuel A. Burden, S. Shankar Sastry. "On the Characterization and Computation of Local Nash Equilibria." 2014.

Journal Papers

Lillian J. Ratliff, Carlos Barreto, Roy Dong, Henrik Ohlsson, Alvaro A. Cárdenas, and S. Shankar Sastry. Effects of Risk on Privacy Contracts for Demand-Side Management. IEEE Transactions on Smart Grid, 2014. Submitted (Sept.) (arXiv:1409.7926v1)

Pushkin Kachroo, Lillian J. Ratliff, and S. Shankar Sastry. "Analysis of the Godunov Based Hybrid Model for Ramp Metering and Robust Feedback Control Design." IEEE Transactions on Intelligent Transportation Systems, Vol. 15, Issue 5, 2132-2142, Oct. 2014. ( PDF)

Roy Dong, Alvaro A. Cárdenas, Lillian J. Ratliff, Henrik Ohlsson, Shankar Sastry. "Quantifying the Utility-Privacy Tradeoff in the Smart Grid." IEEE Transactions on Smart Grid, 2014. Under Review (May). ( arXiv:1406.2568v1)

Pushkin Kachroo, Lillian J. Ratliff, and S. Shankar Sastry. "A New Static Traffic Assignment Using Density Based Travel Time." Applied Mathematical Modeling, 2014. Under Review (July).

Refereed Conference Papers

Ming Jin, Lillian J. Ratliff, Ioannis C. Konstantakopoulos, Costas Spanos, S. Shankar Sastry. "REST: A Reliable Estimation and Stopping Time Algorithm for Social Game Experiments." ICCPS, 2015. Submitted

Lillian J. Ratliff, Ming Jin, Ioannis C. Konstantakopoulos, Costas Spanos, S. Shankar Sastry. "Social Game for Building Energy Efficiency: Incentive Design." Allerton, 2014. ( PDF, Slides)

Lillian J. Ratliff, Roy Dong, Henrik Ohlsson, Alvaro A. Cardenas, Shankar Sastry. "Privacy and Customer Segmentation in the Smart Grid." CDC, 2014. To Appear. ( PDF)

Lillian J. Ratliff, Roy Dong, Henrik Ohlsson, S. Shankar Sastry. "Incentive Design and Utility Learning via Energy Disaggregation." IFAC, 2014. (PDF)

Daniel J. Calderone, Lillian J. Ratliff, Shankar Sastry. "Pricing for Coordination in Open-Loop Differential Games." IFAC, 2014. (PDF)

Henrik Ohlsson, Lillian J. Ratliff, Roy Dong, S. Shankar Sastry. "Blind Identification via Lifting." IFAC, 2014. (PDF)

Roy Dong, Lillian J. Ratliff, Henrik Ohlsson, Shankar Sastry. "Fundamental Limits of Non-Intrusive Load Monitoring." Conference on High Confidence Networked Systems (HiCoNS), 2014. DOI: 10.1145/2566468.2566471 (arXiv)

Lillian J. Ratliff, Samuel A. Burden, Shankar Sastry. "Genericity and Structural Stability of Non-degenerate Differential Nash Equilibria." American Control Conference, 2014. DOI: 10.1109/ACC.2014.6858848

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. DOI: 10.1109/Allerton.2013.6736623 (PDF, Slides)

Roy Dong, Lillian J. Ratliff, Henrik Ohlsson, S. Shankar Sastry. "Energy Disaggregation via Adaptive Filtering." 51st Annual Allerton Conference on Communication, Control, and Computing, 2013. DOI: 10.1109/Allerton.2013.6736521 (arXiv)

Roy Dong, Lillian J. Ratliff, Henrik Ohlsson, Shankar Sastry. "A Dynamical Systems Approach to Energy Disaggregation." IEEE Conference on Decision and Control, 2013. pg. 6335-6340. DOI: 10.1109/CDC.2013.6760891 (arXiv, PDF)

Daniel Calderone, Lillian J. Ratliff, S. Shankar Sastry. "Pricing Design for Robustness in Linear-Quadratic Dynamic Games." IEEE Conference on Decision and Control, 2013. DOI: 10.1109/CDC.2013.6760558

Aaron Bestick, Lillian J. 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 J. Ratliff, Daniel Calderone, Claire Tomlin, S. Shankar Sastry. "Energy Management via Pricing in LQ Dynamic Games." American Control Conference, 2013. DOI: 10.1109/ACC.2013.6579877 (PDF)

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

Lillian J. Ratliff and Pushkin Kachroo. "Validating numerically consistent macroscopic traffic models using microscopic data." 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." ASME Conference Proceedings, 2006.

Tech Reports and Extended Abstracts

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

Lillian J. Ratliff, Roy Dong, Henrik Ohlsson, and S. Shankar Sastry. Energy Efficiency via Incentive Design and Utility Learning. HiCoNS, 2014. DOI: 10.1145/2566468.2576849 (PDF)

Posters

Lillian J. Ratliff, Samuel A. Burden, S. Shankar Sastry. "Characterization and Computation of Local Nash Equilibria in Continuous Games." at TRUST Annual Conference, Washington, D.C. April, 2013. (PDF)

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)

Awards

NSF Graduate Fellowship, 2009

Past Research

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MS thesis topic: Uncertainty Propagation in Dynamical Systems.

Advisor: Pushkin Kachroo