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[1] A. C. Pigou. Economics of welfare , 1920 .
[2] J. G. Wardrop,et al. Some Theoretical Aspects of Road Traffic Research , 1952 .
[3] T. Koopmans,et al. Studies in the Economics of Transportation. , 1956 .
[4] T. Koopmans,et al. Studies in the Economics of Transportation. , 1956 .
[5] G. Stampacchia,et al. On some non-linear elliptic differential-functional equations , 1966 .
[6] G. Hardin,et al. The Tragedy of the Commons , 1968, Green Planet Blues.
[7] Dietrich Braess,et al. Über ein Paradoxon aus der Verkehrsplanung , 1968, Unternehmensforschung.
[8] W. Vickrey. Congestion Theory and Transport Investment , 1969 .
[9] G. Stampacchia,et al. Convex programming and variational inequalities , 1972 .
[10] R. Rosenthal. A class of games possessing pure-strategy Nash equilibria , 1973 .
[11] R. Lewontin. ‘The Selfish Gene’ , 1977, Nature.
[12] Stella Dafermos,et al. Traffic Equilibrium and Variational Inequalities , 1980 .
[13] D. Kinderlehrer,et al. An introduction to variational inequalities and their applications , 1980 .
[14] D. Bertsekas,et al. Projection methods for variational inequalities with application to the traffic assignment problem , 1982 .
[15] Stella Dafermos,et al. An iterative scheme for variational inequalities , 1983, Math. Program..
[16] Thomas L. Magnanti,et al. Network Design and Transportation Planning: Models and Algorithms , 1984, Transp. Sci..
[17] Moshe Ben-Akiva,et al. Discrete Choice Analysis: Theory and Application to Travel Demand , 1985 .
[18] D. McFadden. The Choice Theory Approach to Market Research , 1986 .
[19] Mark D. Uncles,et al. Discrete Choice Analysis: Theory and Application to Travel Demand , 1987 .
[20] Terry L. Friesz,et al. Sensitivity Analysis for Equilibrium Network Flow , 1988, Transp. Sci..
[21] A. Nagurney. Migration equilibrium and variational inequalities. , 1989, Economics letters.
[22] Terry L. Friesz,et al. Sensitivity analysis based heuristic algorithms for mathematical programs with variational inequality constraints , 1990, Math. Program..
[23] Stella Dafermos,et al. General economic equilibrium and variational inequalities , 1991, Oper. Res. Lett..
[24] Anna Nagurney,et al. A network equilibrium formulation of market disequilibrium and variational inequalities , 1991, Networks.
[25] A. Nagurney. Network Economics: A Variational Inequality Approach , 1992 .
[26] Thomas L. Magnanti,et al. Sensitivity Analysis for Variational Inequalities , 1992, Math. Oper. Res..
[27] Michael Mesterton-Gibbons,et al. An introduction to game-theoretic modelling , 2019 .
[28] Masao Fukushima,et al. A globally convergent Newton method for solving strongly monotone variational inequalities , 1993, Math. Program..
[29] P. Marcotte,et al. On the convergence of projection methods: Application to the decomposition of affine variational inequalities , 1995 .
[30] R. Jayakrishnan,et al. A FASTER PATH-BASED ALGORITHM FOR TRAFFIC ASSIGNMENT , 1994 .
[31] Torbjörn Larsson,et al. A class of gap functions for variational inequalities , 1994, Math. Program..
[32] L. Shapley,et al. Potential Games , 1994 .
[33] K. Basu. Stackelberg equilibrium in oligopoly: An explanation based on managerial incentives , 1995 .
[34] Bethany L. Nicholson,et al. Mathematical Programs with Equilibrium Constraints , 2021, Pyomo — Optimization Modeling in Python.
[35] Avi Pfeffer,et al. Representations and Solutions for Game-Theoretic Problems , 1997, Artif. Intell..
[36] Hai Yang,et al. Models and algorithms for road network design: a review and some new developments , 1998 .
[37] Christos H. Papadimitriou,et al. Worst-case Equilibria , 1999, STACS.
[38] A. Rivlin,et al. Economic Choices , 2001 .
[39] Michael Patriksson,et al. A Mathematical Model and Descent Algorithm for Bilevel Traffic Management , 2002, Transp. Sci..
[40] Michael P. Wellman,et al. Learning payoff functions in infinite games , 2005, Machine Learning.
[41] Sarit Kraus,et al. Deployed ARMOR protection: the application of a game theoretic model for security at the Los Angeles International Airport , 2008, AAMAS.
[42] Vincent Conitzer,et al. Learning and Approximating the Optimal Strategy to Commit To , 2009, SAGT.
[43] Heinrich von Stackelberg. Market Structure and Equilibrium , 2010 .
[44] Francisco Facchinei,et al. Convex Optimization, Game Theory, and Variational Inequality Theory , 2010, IEEE Signal Processing Magazine.
[45] Mingyan Liu,et al. Price of Anarchy for Congestion Games in Cognitive Radio Networks , 2012, IEEE Transactions on Wireless Communications.
[46] Justin Domke,et al. Generic Methods for Optimization-Based Modeling , 2012, AISTATS.
[47] Ariel D. Procaccia,et al. Learning Optimal Commitment to Overcome Insecurity , 2014, NIPS.
[48] Rong Yang,et al. Adaptive resource allocation for wildlife protection against illegal poachers , 2014, AAMAS.
[49] J. Zico Kolter,et al. OptNet: Differentiable Optimization as a Layer in Neural Networks , 2017, ICML.
[50] Rachna,et al. Sapiens: A brief history of humankind , 2017 .
[51] Lei Xu,et al. Input Convex Neural Networks : Supplementary Material , 2017 .
[52] S. Shankar Sastry,et al. Markov Decision Process Routing Games , 2017, 2017 ACM/IEEE 8th International Conference on Cyber-Physical Systems (ICCPS).
[53] Joel Z. Leibo,et al. Multi-agent Reinforcement Learning in Sequential Social Dilemmas , 2017, AAMAS.
[54] J. Zico Kolter,et al. What game are we playing? End-to-end learning in normal and extensive form games , 2018, IJCAI.
[55] Fei Fang. Integrating Learning with Game Theory for Societal Challenges , 2019, IJCAI.
[56] Francesca Parise,et al. A variational inequality framework for network games: Existence, uniqueness, convergence and sensitivity analysis , 2017, Games Econ. Behav..
[57] Stephen P. Boyd,et al. Differentiating through a cone program , 2019, Journal of Applied and Numerical Optimization.
[58] Kim D. Listmann,et al. Deep Lagrangian Networks for end-to-end learning of energy-based control for under-actuated systems , 2019, 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).
[59] Sergio Valcarcel Macua,et al. Coordinating the Crowd: Inducing Desirable Equilibria in Non-Cooperative Systems , 2019, AAMAS.
[60] Stephen P. Boyd,et al. Differentiable Convex Optimization Layers , 2019, NeurIPS.
[61] Zhengyuan Zhou,et al. Learning in games with continuous action sets and unknown payoff functions , 2019, Math. Program..
[62] Stephen P. Boyd,et al. Differentiating Through a Conic Program , 2019 .
[63] Nando de Freitas,et al. Social Influence as Intrinsic Motivation for Multi-Agent Deep Reinforcement Learning , 2018, ICML.
[64] David C. Parkes,et al. The AI Economist: Improving Equality and Productivity with AI-Driven Tax Policies , 2020, ArXiv.
[65] Zhuoran Yang,et al. Pontryagin Differentiable Programming: An End-to-End Learning and Control Framework , 2019, NeurIPS.
[66] Roberto Cominetti,et al. When Is Selfish Routing Bad? The Price of Anarchy in Light and Heavy Traffic , 2017, Oper. Res..
[67] Fei Fang,et al. Artificial Intelligence for Social Good: A Survey , 2020, ArXiv.