Journal ArticleDOI
Multi-agent reinforcement learning: weighting and partitioning
Ron Sun,Todd Peterson +1 more
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TLDR
The article presents some ideas regarding weighting of multiple agents and extends them into partitioning an input/state space into multiple regions with differential weighting to reduce the learning complexity of agents (and their function approximators) and thus to facilitate the learning overall.About:
This article is published in Neural Networks.The article was published on 1999-06-01. It has received 75 citations till now. The article focuses on the topics: Learning classifier system & Reinforcement learning.read more
Citations
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Cognitive Radio An Integrated Agent Architecture for Software Defined Radio
TL;DR: This article briefly reviews the basic concepts about cognitive radio CR, and the need for software-defined radios is underlined and the most important notions used for such.
Proceedings Article
Cognitive radio
TL;DR: Cognitive radios, with the capabilities to sense the operating environment, learn and adapt in real time according to environment creating a form of mesh network, are seen as a promising technology.
Proceedings Article
Hybrid reward architecture for reinforcement learning
TL;DR: A new method is proposed, called Hybrid Reward Architecture (HRA), which takes as input a decomposed reward function and learns a separate value function for each component reward function, enabling more effective learning.
Journal ArticleDOI
Ensemble Algorithms in Reinforcement Learning
Marco A. Wiering,H. van Hasselt +1 more
TL;DR: Several ensemble methods that combine multiple different reinforcement learning (RL) algorithms in a single agent to enhance learning speed and final performance by combining the chosen actions or action probabilities of different RL algorithms are described.
Journal ArticleDOI
Machine Learning-Based Fault Diagnosis for Single- and Multi-Faults in Induction Motors Using Measured Stator Currents and Vibration Signals
TL;DR: A novel curve fitting technique is developed to calculate features for the motors that stator currents or vibration signals under certain loadings are not tested for a particular fault, and can accurately detect single- or multi-electrical and mechanical faults in induction motors.
References
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Journal ArticleDOI
Fuzzy identification of systems and its applications to modeling and control
T. Takagi,Michio Sugeno +1 more
TL;DR: A mathematical tool to build a fuzzy model of a system where fuzzy implications and reasoning are used is presented and two applications of the method to industrial processes are discussed: a water cleaning process and a converter in a steel-making process.
Journal ArticleDOI
Induction of Decision Trees
TL;DR: In this paper, an approach to synthesizing decision trees that has been used in a variety of systems, and it describes one such system, ID3, in detail, is described, and a reported shortcoming of the basic algorithm is discussed.
Journal ArticleDOI
Bagging predictors
TL;DR: Tests on real and simulated data sets using classification and regression trees and subset selection in linear regression show that bagging can give substantial gains in accuracy.
Book
Dynamic Programming
TL;DR: The more the authors study the information processing aspects of the mind, the more perplexed and impressed they become, and it will be a very long time before they understand these processes sufficiently to reproduce them.
Proceedings Article
Experiments with a new boosting algorithm
Yoav Freund,Robert E. Schapire +1 more
TL;DR: This paper describes experiments carried out to assess how well AdaBoost with and without pseudo-loss, performs on real learning problems and compared boosting to Breiman's "bagging" method when used to aggregate various classifiers.