eng
Schloss Dagstuhl – Leibniz-Zentrum für Informatik
Leibniz International Proceedings in Informatics
1868-8969
2020-01-06
18:1
18:19
10.4230/LIPIcs.ITCS.2020.18
article
Tarski’s Theorem, Supermodular Games, and the Complexity of Equilibria
Etessami, Kousha
1
Papadimitriou, Christos
2
Rubinstein, Aviad
3
Yannakakis, Mihalis
4
School of Informatics, University of Edinburgh, UK
Dept. of Computer Science, Columbia University, NY, USA
Dept. of Computer Science, Stanford University, CA, USA
Dept of Computer Science, Columbia University, NY, USA
The use of monotonicity and Tarski’s theorem in existence proofs of equilibria is very widespread in economics, while Tarski’s theorem is also often used for similar purposes in the context of verification. However, there has been relatively little in the way of analysis of the complexity of finding the fixed points and equilibria guaranteed by this result. We study a computational formalism based on monotone functions on the d-dimensional grid with sides of length N, and their fixed points, as well as the closely connected subject of supermodular games and their equilibria. It is known that finding some (any) fixed point of a monotone function can be done in time log^d N, and we show it requires at least log^2 N function evaluations already on the 2-dimensional grid, even for randomized algorithms. We show that the general Tarski problem of finding some fixed point, when the monotone function is given succinctly (by a boolean circuit), is in the class PLS of problems solvable by local search and, rather surprisingly, also in the class PPAD. Finding the greatest or least fixed point guaranteed by Tarski’s theorem, however, requires d ⋅ N steps, and is NP-hard in the white box model. For supermodular games, we show that finding an equilibrium in such games is essentially computationally equivalent to the Tarski problem, and finding the maximum or minimum equilibrium is similarly harder. Interestingly, two-player supermodular games where the strategy space of one player is one-dimensional can be solved in O(log N) steps. We also show that computing (approximating) the value of Condon’s (Shapley’s) stochastic games reduces to the Tarski problem. An important open problem highlighted by this work is proving a Ω(log^d N) lower bound for small fixed dimension d ≥ 3.
https://drops.dagstuhl.de/storage/00lipics/lipics-vol151-itcs2020/LIPIcs.ITCS.2020.18/LIPIcs.ITCS.2020.18.pdf
Tarski’s theorem
supermodular games
monotone functions
lattices
fixed points
Nash equilibria
computational complexity
PLS
PPAD
stochastic games
oracle model
lower bounds