3 research outputs found
On the Convergence Time of the Best Response Dynamics in Player-specific Congestion Games
We study the convergence time of the best response dynamics in
player-specific singleton congestion games. It is well known that this dynamics
can cycle, although from every state a short sequence of best responses to a
Nash equilibrium exists. Thus, the random best response dynamics, which selects
the next player to play a best response uniformly at random, terminates in a
Nash equilibrium with probability one. In this paper, we are interested in the
expected number of best responses until the random best response dynamics
terminates.
As a first step towards this goal, we consider games in which each player can
choose between only two resources. These games have a natural representation as
(multi-)graphs by identifying nodes with resources and edges with players. For
the class of games that can be represented as trees, we show that the
best-response dynamics cannot cycle and that it terminates after O(n^2) steps
where n denotes the number of resources. For the class of games represented as
cycles, we show that the best response dynamics can cycle. However, we also
show that the random best response dynamics terminates after O(n^2) steps in
expectation.
Additionally, we conjecture that in general player-specific singleton
congestion games there exists no polynomial upper bound on the expected number
of steps until the random best response dynamics terminates. We support our
conjecture by presenting a family of games for which simulations indicate a
super-polynomial convergence time
Approximate Equilibria in Games with Few Players
We study the problem of computing approximate Nash equilibria (epsilon-Nash
equilibria) in normal form games, where the number of players is a small
constant. We consider the approach of looking for solutions with constant
support size. It is known from recent work that in the 2-player case, a
1/2-Nash equilibrium can be easily found, but in general one cannot achieve a
smaller value of epsilon than 1/2. In this paper we extend those results to the
k-player case, and find that epsilon = 1-1/k is feasible, but cannot be
improved upon. We show how stronger results for the 2-player case may be used
in order to slightly improve upon the epsilon = 1-1/k obtained in the k-player
case