Overview of Topics

R. Chandan, D. Paccagnan, and J.R. Marden, "The Pareto Frontier of Inefficiency in Congestion Games," working paper, 2021.

K. Paarporn, R. Chandan, M. Alizadeh, and J.R. Marden, "Keep them guessing: Asymmetric information in General Lotto games," working paper, 2021.

R. Chandan, D. Paccagnan, and J.R. Marden, “When Smoothness is Not Enough: Toward Exact Quantification and Optimization of the Price of Anarchy,” 2021 (under review).

D. Paccagnan, R. Chandan, B.L. Ferguson,  and J.R. Marden, "Incentivizing efficient use of shared infrastructure: Optimal tolls in congestion game,"ACM Transactions on Economics and Computation, 2021 (accepted).

B.L. Ferguson and J.R. Marden, “Robust Utility Design in Distributed Resource Allocation Problems with Defective Agents,” 2021 (under review).

R. Konda, R. Chandan, D. Grimsman, and J.R. Marden, “Balancing Asymptotic and Transient Efficiency in Set Covering Games,” 2021 (under review).

R. Konda, R. Chandan, and J.R. Marden, “Mission Level Uncertainty in Multi-Agent Resource Allocation,” 2021 (under review).

K. Paarporn, R. Chandan, M. Alizadeh, J.R. Marden, "The Division of Assets in Multiagent Systems: A Case Study in Team Blotto Games," 2021 (under review).

Y. Yue, B.L. Ferguson, and J.R. Marden, "Incentive Design for Congestion Games with Unincentivizable Users," 2021 (under review).  

B. Ferguson, P.N. Brown, and J.R. Marden, “The Effectiveness of Subsidies and Taxes in Atomic Congestion Games,” IEEE Control Systems Letters, 2021 (to appear).

R. Chandan, D. Paccagnan, and J.R. Marden, "Tractable mechanisms for computing near-optimal utility functions," 20th International Conference on Autonomous Agents and Multiagent Systems, 2021.

J.R. Marden and J.S. Shamma, "Game Theory and Control," Annual Review of Control, Robotics, and Autonomous Systems, 2018.

J.R. Marden and J.S. Shamma, "Game Theoretic Learning in Distributed Control," Handbook of Dynamic Game Theory, 2018.

J.R. Marden and J.S. Shamma, "Game Theory and Distributed Control," Handbook of Game Theory, Volume IV, edited by Peyton Young and Shmuel Zamir, Elsevier Science, 2014.

P.N. Brown and J.R. Marden, “Studies on Robust Social Influence Mechanisms, Incentives for Efficient Network Routing in Uncertain Settings,” IEEE Control Systems Magazine, Volume 37, Issue 1, Pages 98-115, February 2017.

K. Paarporn, R. Chandan, M. Alizadeh, and J.R. Marden, “The Division of Assets in Multiagent Systems: A Case Study in Team Blotto Games,” IEEE Conference on Decision and Control, 2021 (under review).

D. Grimsman, J.P. Hespanha, and J.R. Marden, “Stackelberg Equilibria for Two-Player Network Routing Games on Parallel Networks,” American Control Conference, 2020.

R. Chandan, K. Paarporn, and J.R. Marden. “When showing your hand pays off: Announcing strategic intentions in Colonel Blotto games,” American Control Conference, 2020.

K. Paarporn, R. Chandan, M. Alizadeh and J.R. Marden, “Characterizing the interplay between information and strength in Blotto games,” IEEE Conference on Decision and Control, 2019.

K. Paarporn, B. Canty, P.N. Brown, M. Alizadeh, and J.R. Marden, “The impact of complex and informed adversarial behavior in graphical coordination games,” IEEE Transactions on Control of Networked Systems, Volume 8, Issue 1, Pages 200-211, March, 2021.

K.Paarporn, M.Alizadeh and J.R.Marden, “A risk-security tradeoff in graphical coordination games,” IEEE Transactions on Automatic Control, Volume 66, Issue 5, Pages 1973 - 1985, May, 2021.

P.N. Brown, H. Borowski and J.R. Marden, “Security Against Impersonation Attacks in Distributed Systems,” IEEE Transactions of Networked Control Systems, Volume 6, Issue 1, Pages 440-450, March 2019.

D. Paccagnan, R. Chandan, B.L. Ferguson,  and J.R. Marden, "Incentivizing efficient use of shared infrastructure: Optimal tolls in congestion game,"ACM Transactions on Economics and Computation, 2021 (accepted).

R. Chandan, D. Paccagnan, and J.R. Marden, “When Smoothness is Not Enough: Toward Exact Quantification and Optimization of the Price of Anarchy,” 2021 (under review).

B.L. Ferguson and J.R. Marden, “Robust Utility Design in Distributed Resource Allocation Problems with Defective Agents,” 2021 (under review).

R. Konda, R. Chandan, D. Grimsman, and J.R. Marden, “Balancing Asymptotic and Transient Efficiency in Set Covering Games,” 2021 (under review).

R. Konda, R. Chandan, and J.R. Marden, “Mission Level Uncertainty in Multi-Agent Resource Allocation,” IEEE Conference on Decision and Control, 2021.

V. Ramaswamy, D. Paccagnan and J.R. Marden, “Multiagent Coverage Problems: The Trade-offs Between Anarchy and Stability,” IEEE Transactions on Automatic Control, 2021 (to appear).

D.Paccagnan, R.Chandan, J.R. Marden, “Distributed Resource Allocation Through Utility Design - Part I: Optimizing the Performance Certificates via the Price of Anarchy,” IEEE Transactions on Automatic Control, Volume 65, Issue 11, November 2020.

D.Paccagnan and J.R. Marden, “Distributed Resource Allocation Through Utility Design - Part II: Applications to Submodular, Covering, and Supermodular Problems,” IEEE Transactions on Automatic Control, 2021 (to appear).

D.Paccagnan and J.R. Marden, "The Importance of System-Level Information in Multiagent Systems Design: Cardinality and Covering Problems,” IEEE Transactions on Automatic Control, Volume 64, Issue 8, Pages 3253-3267, August 2019.

P.N. Brown and J.R. Marden, "On the feasibility of local utility redesign for multiagent optimization," in Proceedings of European Control Conference, 2019.

M. Phillips and J.R. Marden, “Design Tradeoffs in Concave Cost Sharing Games,” IEEE Transactions on Automatic Control, Volume 63, Issue 7, Pages 2242-2247, July 2018.

R. Gopalakrishnan, J.R. Marden, and A. Wierman, “Potential Games are Necessary to Ensure Pure Nash Equilibria in Cost Sharing Games,” Mathematics of Operations Research, Volume 39, Number 4, pp. 1252-1296, 2014.

N. Li and J.R. Marden, “Decoupling Coupled Constraints Through Utility Design,” IEEE Transac- tions on Automatic Control, Volume 59, Issue 8, 2014.

J.R. Marden and T. Roughgarden, “Generalized Efficiency Bounds in Distributed Resource Allocation,” IEEE Transactions on Automatic Control, Volume 59, Number 3, 2014.

N. Li and J.R. Marden, “Designing Games for Distributed Optimization,” IEEE Journal of Selected Topics in Signal Processing, special issue on Adaptation and Learning over Complex Networks, Volume 7, Number 2, 2013.

J.R. Marden and A. Wierman, “Distributed Welfare Games,” Operations Research, Volume 61, Issue 1, pp. 155-168, 2013.

J.R. Marden and A. Wierman, “Overcoming The Limitations of Utility Design for Multiagent Systems,” IEEE Transactions on Automatic Control, Volume 58, Number 6, pp. 1402-1415, 2013.

J.R. Marden, “State Based Potential Games,” Automatica, Volume 48, pp. 3075-3088, 2012.

J.R. Marden and M. Effros, “The Price of Selfishness in Network Coding,” IEEE Transactions on Information Theory, Volume 58, Issue 4, pp. 2349-2361, 2012.

B.L. Ferguson, P.N. Brown, and J.R. Marden, “How Information Affects Incentive Design: A Case- Study in Simple Congestion Networks,” 2020, (under review).

B. L. Ferguson, P.N. Brown, and J.R. Marden, "The Effectiveness of Subsidies and Tolls in Congestion Games," 2020 (under review).

Y. Yue, B.L. Ferguson, and J.R. Marden, “Incentive Design for Congestion Games with Unincentivizable Users,” 2021 (under review).

P.N.Brown and JR.Marden, “Can Taxes Improve Congestion on all Networks?”, IEEE Transactions on Control of Networked Systems, Volume 7, Issue 4, Pages 1643 - 1653, December, 2020.

P. N. Brown and J.R. Marden, “Optimal Mechanisms for Robust Coordination in Congestion Games,” IEEE Transactions on Automatic Control, Volume 63, Issue 8, Pages 2437 - 2448,  August 2018.

P.N. Brown and J.R. Marden, “Studies on Robust Social Influence Mechanisms, Incentives for Efficient Network Routing in Uncertain Settings,” IEEE Control Systems Magazine, Volume 37, Issue 1, Pages 98-115, February 2017.

P.N. Brown and J.R. Marden, “The Robustness of Marginal-Cost Taxes in Affine Congestion Games,” IEEE Transactions on Automatic Control, Volume 62, Issue 8, Pages 3999-4004, August 2017.

P.N. Brown and J.R. Marden, "A Study on Price Discrimination for Robust Social Coordination," Proceedings of American Control Conference, 2016.

B.L. Ferguson, P.N. Brown, and J.R. Marden, “How Information Affects Incentive Design: A Case- Study in Simple Congestion Networks,” 2020, (under review).

R. Konda, R. Chandan, and J.R. Marden, “Mission Level Uncertainty in Multi-Agent Resource Allocation,” IEEE Conference on Decision and Control, 2021.

V. Ramaswamy, D. Paccagnan and J.R. Marden, “Multiagent Coverage Problems: The Trade-offs Between Anarchy and Stability,” IEEE Transactions on Automatic Control, 2021 (to appear).

D. Grimsman, M. Kirchner, J.P. Hespanha, and J.R. Marden, “The Impact of Message Passing in Agent-Based Submodular Maximization,” 2020, (under review).

D. Grimsman, M.S. Ali, J.P. Hespanha, and J.R. Marden, “The Impact of Information in Distributed Submodular Maximization,” IEEE Transactions on Control of Networked Systems, Volume 6, Issue 4, December 2019.

J.R. Marden, “The Role of Information in Distributed Resource Allocation,” IEEE Transactions on Control of Networked Systems, Volume 4, Issue 3, Pages 654-664, September 2017.

L. Diang et al., “Learning in Potential Games with Applications to Power Grids: Models, Dynamics, and Outlook,”IEEE Transactions on Industrial Informarahultics, 2020, (under review).

R. Konda, R. Chandan, D. Grimsman, and J.R. Marden, “Balancing Asymptotic and Transient Efficiency in Set Covering Games,” 2021 (under review).

H. Borowski, J.R. Marden, and J.S. Shamma, “Learning to Play Efficient Coarse Correlated Equilibria,” Dynamic Games and Applications, Volume 9, Pages 24–46, 2019.

J.R. Marden, “Selecting Efficient Correlated Equilibria Through Distributed Learning,” Games and Economic Behavior, Volume 106  Pages 114-133, November 2017.

H. Borowski and J.R. Marden, “Fast Convergence in Semi-Anonymous Potential Games,” IEEE Transactions on Control of Networked Systems, Volume 4, Issue 2, Pages 246-258, June 2017.

J.R. Marden, H.P.Young, and L.Y. Pao, “Achieving Pareto Optimality Through Distributed Learning,” SIAM Journal on Control and Optimization, Volume 52, Issue 2, pp. 2753-2770, 2014.  [SIAM/CST Best Sicon Paper Prize]

H. Borowski, J. R. Marden, D. S. Leslie, and E. W. Frew, "Coarse Resistance Tree Methods For Stochastic Stability Analysis," IEEE Conference on Decision and Control, 2013.

J.R. Marden and J.S. Shamma, “Revisiting Log-Linear Learning: Asynchrony, Completeness and a Payoff-based Implementation,” Games and Economic Behavior, Volume 75, Issue 2, July 2012, pp. 788-808.

D. S. Leslie and J. R. Marden, "Equilibrium Selection in Potential Games with Noisy Rewards," Proceedings of NetGCoop, 2011.

J.R. Marden, H.P. Young, G. Arslan, and J.S. Shamma, “Payoff Based Dynamics for Multi-Player Weakly Acyclic Games,” SIAM Journal on Control and Optimization, special issue on “Control and Optimization in Cooperative Networks,” Volume 48, Issue 1, February 2009, pp. 373-396.

J.R. Marden, G. Arslan and J.S. Shamma, “Joint Strategy Fictitious Play with Inertia for Potential Games,” IEEE Transactions on Automatic Control, Volume 54, Issue 2, February 2009, pp. 208-220.

P. Gebraad, F.W. Teeuwisse, J.W. van Wingerden, P.A. Fleming, S.D. Ruben, J.R. Marden, and L.Y. Pao, “Wind plant power optimization through yaw control using a parametric model for wake effects,” Wind Energy, Volume 19, Issue 1, Pages 95-114, January 2016.

N. Li and J.R. Marden, “Decoupling Coupled Constraints Through Utility Design,” IEEE Transactions on Automatic Control, Volume 59, Issue 8, 2014.

N. Li and J.R. Marden, “Designing Games for Distributed Optimization,” IEEE Journal of Selected Topics in Signal Processing, special issue on Adaptation and Learning over Complex Networks, Volume 7, Number 2, 2013.

J.R. Marden, S. Ruben, and L.Y. Pao, “Model-Free Approach to Wind Farm Control Using Game Theoretic Methods,” IEEE Transactions on Control Systems Technology special issue “to tame the wind: advanced control applications in wind energy,” Volume 21, Number 4, pp. 1207-1214, 2013.

J.R. Marden, “State Based Potential Games,” Automatica, Volume 48, pp. 3075-3088, 2012.

R. Gopalakrishnan, J.R. Marden, and A. Wierman, “An architectural view of game theoretic control,” ACM Sigmetrics Performance Evaluation Review, Volume 38, Number 3, 2011, pp. 31-36.

J.R. Marden, G. Arslan and J.S. Shamma, “Cooperative Control and Potential Games,” IEEE Transactions on Systems, Man and Cybernetics. Part B: Cybernetics, Volume 39, Issue 6, December 2009, pp. 1393-1407.

G. Arslan, J.R. Marden and J.S. Shamma, “Autonomous Vehicle-Target Assignment: A Game Theoretical Formulation,” ASME Journal of Dynamic Systems, Measurement and Control, Volume 129, Issue 5, September 2007, pp. 584-596.

H. Chen, J. R. Marden and A. Wierman, "On the Impact of Heterogeneity and Back-end Scheduling in Load Balancing Designs," IEEE Conference on Computer Communications (INFOCOM), March, 2009.

J. R. Marden, "Learning in Large-Scale Games and Cooperative Control", Ph.D. Dissertation, UCLA, Los Angeles, CA, June, 2007.

J. R. Marden, "Coordination of Multiple Agents Using Neuro-Dynamic Programming", MS Thesis, UCLA, Los Angeles, CA, June, 2004.  

Decision-Making in Complex Adversarial Environments

Recent Papers

Book Chapters and Magazine Articles

Mechanism Design for Multiagent Systems

Robust Social Influence

The Role of Information in Multiagent Systems

Learning in Games

Cooperative Control and Applications

Theses

In this paper we break papers out by different topic areas.  Please click here If you prefer to see a list of papers in chronological order.  The main areas area as follows:

Recent Papers: Here is a list of recent papers coming out of the lab.  Most of the paper are currently under submission or recently accepted.  

Book Chapters and Magazine Articles: This papers give a broad background on the role of game theory in distributed control of multiagent systems.

Decision-Making in Complex Adversarial Environments: This literature provides a recent research thrust in decision-making in adversarial enviroments. Specific interest focuses on characterizing the "value of information" in such settings.  The primary domain considered here is Colonel Blotto Games, which are experiencing a resurgence in research attention in the past 5-10 years.  

Mechanism Design for Multiagent Systems:  Mechanism design, or more generally utility design, involves the design of utility functions for the agents in a system of interest. Traditionally, this field has focuses on auction theory where the auctioneer defines the auction, which in turn defines the utility function. However, this field is far broader as utility design is applicable to cooperative control (e.g., the assignment of local objective functions to programmable entities in a multi-agent system) and incentive design in societal bases systems (e.g., taxes in transportation networks).

Robust Social Infuence: This stream of work focuses on the derivation of incentive mechanisms, e.g., taxes or informational broadcasts, geared at influencing self-interested behavior and improving the emergent collective behavior.  Specific interest here is dedicated to robust incentive mechanisms, i.e., incentive mechanisms that are to be implement in systems where there are uncertainties in how self-interested users will respond to such mechanisms.  

The Role of Information in Multiagent Systems: This recent stream of work focuses on identifying the value of information in multiagent systems.  Multi-agent systems operate in environments where individual agents have access to locally avaialble information. The "degree" of this information clearly impacts that potential efficiency guarantees associated with agreeable networked control algorithms that rely on this information.  Accordingly, here we seek to identify how information imposes constraints on achievable performance and what information should be shared amongst the agents to improve these guarantees.     

Learning in Games: This stream of work focuses on the derivation of multi-agent decision making rules that provide guarantees on the resulting asymptotic behaviors.  Specific focus is on equilibrium selection, which involves driving the collective behavior to certain classes of equilibria that maybe more desirable from a societal perspective.

Cooperative Control of Networked Multiagent Systems: This stream of literature focuses on the design of networked control algorithms that ensure the agents resulting collective behavior is efficient with regards to a given system-level objective function. Applications of cooperative control will also be contained within.

Theses: This is where it all began!