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AUTHOR(S): Daschievici Luiza, Ghelase Daniela
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TITLE Reiforcement learning in Cognitive Engineering of Manufacturing processes |
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ABSTRACT The researches about learning in the word pointed out the fact that a crucial role it own the interaction with environment. The practice of sensory connections with the environment produces a big quantity of information of type cause-effect about the consequences of actions and adequate decisions for the touch of the aims. These information are a major source of knowledge about environment. In each moment, we are conscious of manner in which the environment reacts at our actions and we search to influence this thing through our behavior. The interaction is the fundamentally cause of the theories about learn and intelligence. Learning process, in general, is a process, in abaft whom, the agent (he who learn) improves the capacity of act, so that, in temporally of next solicitations, the agent undertakes actions with big efficient. The cognitive approaching is based on acknowledge continue of the situations and the decisions in real-time about activities. Thus can offer solutions for develop and competitiveness of the manufacturing systems based on theories about knowledge and complexity. Cognitive management in manufacturing systems is characterized through the ability to perceive the environment, take the decision on time, in behind of interactions, haven’t specific procedures. |
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KEYWORDS competitiveness, cognitive engineering, reinforcement learning |
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Cite this paper Daschievici Luiza, Ghelase Daniela. (2020) Reiforcement learning in Cognitive Engineering of Manufacturing processes. International Journal of Mechanical Engineering, 5, 56-63 |
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