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Efficient Exploration in Reinforcement Learning Based on Utile Suffix Memory
TLDR
We consider different exploration techniques applied to the learning algorithm “Utile Suffix Memory”, and, in addition, discuss an adaptive fringe depth. Expand
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Athens Neutron Monitor and its aspects in the cosmic-ray variations studies
After many years break (since the 1978) the Athens Neutron Monitor renewed its operation due to joint efforts of Athens University (Greece) and IZMIRAN (Russia). In the present work the short historyExpand
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Orientation of discontinuities in the metal of power-generating equipment
The method of comparison of second central normalized moments of the nominal heights of a discontinuity and a cylindrical reflector is shown to be suitable for determining the configuration of anExpand
LOCAL GOALS DRIVEN HIERARCHICAL REINFORCEMENT LEARNING*
Efficient exploration is of fundamental importance for autonomous agents that learn to act. Previous approaches to exploration in reinforcement learning usually address exploration in the case whenExpand
SELF-ORGANIZING IN NEURAL NETWORKS BASED ON MEMORIZING
The goal of artificial intelligence is to develop a system that could deal with intelligent tasks in autonomous way. This goal is not achieved, but through this research many interesting algorithmsExpand
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Efficient Exploration in Reinforcement Learning Based on Short-term Memory
Reinforcement learning addresses the question of how an autonomous agent that senses and acts in its environment can learn to choose optimal actions to achieve its goals. It is related to the problemExpand
GENERAL ASPECTS OF CONSTRUCTING AN AUTONOMOUS ADAPTIVE AGENT
There are a great deal of approaches in artificial intelligence, some of them also coming from biology and neirophysiology. In this paper we are making a review, discussing many of them, andExpand