One of the most famous examples is AlphaGo, a computer program developed by Google’s subsidiary DeepMind Technologies. In the past, board games like chess and Go were testbeds of deep RL algorithms. The technology behind is the RL, a type of machine learning paradigm where developers reward behaviors they wish the AI to manifest and the program trains or learns itself by performing the necessary actions to achieve the desired behavior or outcome. Like human players, computer game agents are becoming more intelligent as they experience new behaviors and process the appropriate sequence of actions. ![]() Their victory came after spending five months processing the source code and exploring the architecture to compete against 19 teams from top Chinese universities. “In the beginning, we couldn’t even set up the game environment, let alone train the AI agent to play games,” team member Chen Huayu said, adding that his fellow team members were already keen players of HOK. The winning team, composed of five students from Tsinghua University, said the theoretical capabilities of the RL model were not as easy as imagined when put into practice. The second AI Arena Multi-agent Reinforcement Learning Competition in China, which ended in April, saw vibrant groups of student developers who built reinforcement learning (RL)-based AI algorithms that can be used to play the HOK autonomously. While being one of the most popular mobile games of all time, what is lesser-known is that Honor of Kings is often used as an ideal testbed for AI research in the games industry. The official trailer for the new Honor of Kings (HOK) has recently been released, creating a lot of buzz among its global fans who are waiting for the game's release at the end of this year.ĭeveloped by Tencent Games’ TiMi Studio Group, the mobile game has been among the most popular multiplayer online battle arena (MOBA) games since 2015.
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