Crowd Simulation Via Multi-Agent Reinforcement Learning
نویسنده
چکیده
Artificial intelligence is frequently used to control virtual characters in movies and games. When these characters appear in crowds, controlling them is called crowd simulation. In this paper, I suggest that crowd simulation could be accomplished by multi-agent reinforcement learning, a method by which groups of agents can learn to act autonomously in their environment. I present a case study that explores the challenges and benefits of this type of approach and encourages the development of learning techniques for AI in enter-
منابع مشابه
Learning Crowd Behaviour with Neuroevolution Master ’ s thesis Pascal
Many different techniques are used to mimic human behaviour in order to create realistic crowd simulations. Agent-based approaches, while having the most potential for realism, traditionally required carefully hand-crafted rules. In recent years the focus has shifted from hand-crafting decision rules to learning them through methods such as reinforcement learning. In this work a closer look is ...
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