Convergence of Gradient Dynamics with a Variable Learning Rate

  title={Convergence of Gradient Dynamics with a Variable Learning Rate},
  author={Michael H. Bowling and Manuela M. Veloso},
As multiagent environments become more prevalent we need to understand how this changes the agent-based paradigm. One aspect that is heavily affected by the presence of multiple agents is learning. Traditional learning algorithms have core assumptions, such as Markovian transitions, which are violated in these environments. Yet, understanding the behavior of learning algorithms in these domains is critical. Singh, Kearns, and Mansour (2000) examine gradient ascent learning, specifically within… CONTINUE READING
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Publications referenced by this paper.
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Classics in game theory

Kuhn, H. W. Ed

Differential equations: Foundations and applications

H. Reinhard
McGraw Hill Text • 1987
View 2 Excerpts

An iterative method of solving a game

J. Robinson
Annals of Mathematics, • 1951
View 1 Excerpt

Equilibrium Points in N-Person Games.

Proceedings of the National Academy of Sciences of the United States of America • 1950

Equilibrium points in

Nash, J. F.

Equilibrium points in nperson games

M. J. Osborne, A. Rubinstein
PNAS • 1950

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