Generalized pursuit learning schemes: New families of continuous and discretized learning automata
M Agache, BJ Oommen - IEEE Transactions on Systems, Man …, 2002 - ieeexplore.ieee.org
The fastest learning automata (LA) algorithms currently available fall in the family of
estimator algorithms introduced by Thathachar and Sastry (1986). The pioneering work of …
estimator algorithms introduced by Thathachar and Sastry (1986). The pioneering work of …
Stochastic learning-based weak estimation of multinomial random variables and its applications to pattern recognition in non-stationary environments
In this paper, we formally present a novel estimation method, referred to as the Stochastic
Learning Weak Estimator (SLWE), which yields the estimate of the parameters of a binomial …
Learning Weak Estimator (SLWE), which yields the estimate of the parameters of a binomial …
A new approach to the design of reinforcement schemes for learning automata: Stochastic estimator learning algorithms
GI Papadimitriou - IEEE Transactions on Knowledge and Data …, 1994 - ieeexplore.ieee.org
A new class of learning automata is introduced. The new automata use a stochastic
estimator and are able to operate in nonstationary environments with high accuracy and a …
estimator and are able to operate in nonstationary environments with high accuracy and a …
Fast and epsilon-optimal discretized pursuit learning automata
Learning automata (LA) are powerful tools for reinforcement learning. A discretized pursuit
LA is the most popular one among them. During an iteration its operation consists of three …
LA is the most popular one among them. During an iteration its operation consists of three …
A new continuous action-set learning automaton for function optimization
H Beigy, MR Meybodi - Journal of the Franklin Institute, 2006 - Elsevier
In this paper, we study an adaptive random search method based on continuous action-set
learning automaton for solving stochastic optimization problems in which only the noise …
learning automaton for solving stochastic optimization problems in which only the noise …
Adaptive data broadcasting in underwater wireless networks
P Nicopolitidis, GI Papadimitriou… - IEEE Journal of …, 2010 - ieeexplore.ieee.org
Underwater acoustic networks have recently emerged as a new area of research in wireless
networking. These networks can support a large number of applications such as …
networking. These networks can support a large number of applications such as …
The hierarchical continuous pursuit learning automation: a novel scheme for environments with large numbers of actions
Although the field of learning automata (LA) has made significant progress in the past four
decades, the LA-based methods to tackle problems involving environments with a large …
decades, the LA-based methods to tackle problems involving environments with a large …
A new class of/spl epsi/-optimal learning automata
GI Papadimitriou, M Sklira… - IEEE Transactions on …, 2004 - ieeexplore.ieee.org
A new class of P-model absorbing learning automata is introduced. The proposed automata
are based on the use of a stochastic estimator in order to achieve a rapid and accurate …
are based on the use of a stochastic estimator in order to achieve a rapid and accurate …
Learning automata-based bus arbitration for shared-medium ATM switches
MS Obaidat, GI Papadimitriou… - … on Systems, Man …, 2002 - ieeexplore.ieee.org
Although new high-bandwidth network technologies are being introduced and widely
deployed, asynchronous transfer mode (ATM) is still considered one of the most important …
deployed, asynchronous transfer mode (ATM) is still considered one of the most important …
A novel strategy for solving the stochastic point location problem using a hierarchical searching scheme
Stochastic point location (SPL) deals with the problem of a learning mechanism (LM)
determining the optimal point on the line when the only input it receives are stochastic …
determining the optimal point on the line when the only input it receives are stochastic …