Sciweavers

945 search results - page 15 / 189
» Dialog Convergence and Learning
Sort
View
SIAMCO
2000
117views more  SIAMCO 2000»
14 years 9 months ago
The O.D.E. Method for Convergence of Stochastic Approximation and Reinforcement Learning
It is shown here that stability of the stochastic approximation algorithm is implied by the asymptotic stability of the origin for an associated ODE. This in turn implies convergen...
Vivek S. Borkar, Sean P. Meyn
ESANN
2003
14 years 11 months ago
Accelerating the convergence speed of neural networks learning methods using least squares
In this work a hybrid training scheme for the supervised learning of feedforward neural networks is presented. In the proposed method, the weights of the last layer are obtained em...
Oscar Fontenla-Romero, Deniz Erdogmus, José...
93
Voted
ICML
2000
IEEE
15 years 10 months ago
Convergence Problems of General-Sum Multiagent Reinforcement Learning
Stochastic games are a generalization of MDPs to multiple agents, and can be used as a framework for investigating multiagent learning. Hu and Wellman (1998) recently proposed a m...
Michael H. Bowling
NIPS
2008
14 years 11 months ago
Temporal Difference Based Actor Critic Learning - Convergence and Neural Implementation
Actor-critic algorithms for reinforcement learning are achieving renewed popularity due to their good convergence properties in situations where other approaches often fail (e.g.,...
Dotan Di Castro, Dmitry Volkinshtein, Ron Meir
FUZZIEEE
2007
IEEE
15 years 4 months ago
Fuzzy Approximation for Convergent Model-Based Reinforcement Learning
— Reinforcement learning (RL) is a learning control paradigm that provides well-understood algorithms with good convergence and consistency properties. Unfortunately, these algor...
Lucian Busoniu, Damien Ernst, Bart De Schutter, Ro...