Crowd Simulation Via Multi-Agent Reinforcement Learning

Autor:	Lisa Torrey
Rok vydání:	2010
Zdroj:	Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment. 6:89-94
ISSN:	2334-0924 2326-909X
DOI:	10.1609/aiide.v6i1.12390
Popis:	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 entertainment media.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::96612d107794b0c59965934749eab670 https://doi.org/10.1609/aiide.v6i1.12390 Zobrazit plný text záznamu