Accepted Papers

  • Designing a decision tree for Cross-device communication technology aimed at iOS and Android developers
    Chioino Salom¡­on, Jamil , Contreras Celis, Ivan y, Barrientos Padilla, Alfredoz, Garnique Vives, Luisx,Universidad Peruana de Ciencias Aplicadas,Peru

    Pong game was the titanic of the gaming industry in 20th century. Pong is the perfect example of deep reinforcement learning of ATARI game [1]. The game is extremely beneficial to improve concentration and memory capacity. Since the game is played by around 350 million people worldwide at present scenario, hence we saw the opportunity in this interesting game.]The project has a great scope in atari game development. We proposed a stochastic reinforcement learning technique of Policy Gradient algorithm to optimize Pong game . The purpose of this study is to improve the algorithms that control the game structure, mechanism and real-time dynamics. We implemented policy gradient algorithm to improve the performance and training which is significantly better than traditional genetic algorithm.