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ATAL
2009
Springer
15 years 6 months ago
Multiagent reinforcement learning: algorithm converging to Nash equilibrium in general-sum discounted stochastic games
This paper introduces a multiagent reinforcement learning algorithm that converges with a given accuracy to stationary Nash equilibria in general-sum discounted stochastic games. ...
Natalia Akchurina
CEC
2008
IEEE
15 years 6 months ago
New evaluation criteria for the convergence of continuous evolutionary algorithms
—The first hitting time (FHT) plays an important role in convergence evaluation for evolutionary algorithms. However, the current criteria of the FHT are mostly under a hypothesi...
Ying Lin, Jian Huang, Jun Zhang
ICASSP
2008
IEEE
15 years 6 months ago
Distributed average consensus with increased convergence rate
The average consensus problem in the distributed signal processing context is addressed by linear iterative algorithms, with asymptotic convergence to the consensus. The convergen...
Boris N. Oreshkin, Tuncer C. Aysal, Mark Coates
ISCAS
2007
IEEE
149views Hardware» more  ISCAS 2007»
15 years 6 months ago
Convergence Analysis of the Unscented Kalman Filter for Filtering Noisy Chaotic Signals
— The unscented Kalman filter (UKF) has recently been proposed for filtering noisy chaotic signals. Though computationally advantageous, the UKF has not been thoroughly analyze...
Jiuchao Feng, Hongjuan Fan, Chi K. Michael Tse
ECML
2005
Springer
15 years 5 months ago
Towards Finite-Sample Convergence of Direct Reinforcement Learning
Abstract. While direct, model-free reinforcement learning often performs better than model-based approaches in practice, only the latter have yet supported theoretical guarantees f...
Shiau Hong Lim, Gerald DeJong