فهرس المقالات Q_learning

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  1 - Soccer Goalkeeper Task Modeling and Analysis by Petri Nets
  Azadeh Gholami Bahram Sadeghi Bigham
  In a robotic soccer team, goalkeeper is an important challenging role, which has different characteristics from the other teammates. This paper proposes a new learning-based behavior model for a soccer goalkeeper robot by using Petri nets. The model focuses on modeling أکثر

  In a robotic soccer team, goalkeeper is an important challenging role, which has different characteristics from the other teammates. This paper proposes a new learning-based behavior model for a soccer goalkeeper robot by using Petri nets. The model focuses on modeling and analyzing, both qualitatively and quantitatively, for the goalkeeper role so that we have a model-based knowledge of the task performance in different possible situations. The different primitive actions and behaviors as well as the events to switch between them, and also environment models were designed and implemented. For this purpose, a modeling and analysis framework based on Petri nets is used, which enables modeling a robot task, analyzing its qualitative and quantitative properties and using the Petri net representation for actual plan execution. The proposed model building blocks and some tasks of robot are detailed. The novelty of approach is considering some alternatives through tasks execution, which are implemented by conflicts in their Petri net models, and also Q_learning employment in these decision points in order to learn the best policy. Therefore, the execution of actions in different tasks will be controlled effectively. The results of theoretical analysis of some case studies show impressive performance improvement in goalkeeper task execution. تفاصيل المقالة
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  2 - Using Reinforcement Learning to Make Smart Energy Storage Source in Microgrid
  Sadegh Etemad Nasser Mozayani
  The use of renewable energy in power generation and sudden changes in load and fault in power transmission lines may cause a voltage drop in the system and challenge the reliability of the system. One way to compensate the changing nature of renewable energies in the sh أکثر

  The use of renewable energy in power generation and sudden changes in load and fault in power transmission lines may cause a voltage drop in the system and challenge the reliability of the system. One way to compensate the changing nature of renewable energies in the short term without the need to disconnect loads or turn on other plants, is the use of renewable energy storage. The use of energy storage improved electrical stability, power quality and improve the peak power load. In this paper, we have used the reinforcement learning to present an optimal method for charge and discharge the consumer battery. In this way the uncertainty of production due to the random nature of wind energy is improved. Simulation results indicate not only the use of renewable energy and battery is successfully enhanced but also the cost of annual payments and peak consumption times is reduced. تفاصيل المقالة