Virtual reality, art, and entertainment
Presence: Teleoperators and Virtual Environments - Premier issue
Guiding interactive drama
Reinforcement learning for declarative optimization-based drama management
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
Targeting specific distributions of trajectories in MDPs
AAAI'06 proceedings of the 21st national conference on Artificial intelligence - Volume 2
Another look at search-based drama management
Proceedings of the 7th international joint conference on Autonomous agents and multiagent systems - Volume 3
Another look at search-based drama management
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 2
Personalised pathway prediction
UMAP'10 Proceedings of the 18th international conference on User Modeling, Adaptation, and Personalization
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In this paper, we address the problem of building a system of autonomous agents for a complex environment, in our case, a museum with many visitors. Visitors may have varying preferences for types of art or may wish to visit different exhibits on multiple visits. Often, these goals conflict. For example, many visitors may wish to see the museum's most popular work, but that could cause congestion, ruining the experience. Thus, our task is to build a set of agents that can satisfy their visitors' goals, while simultaneously providing high quality experiences for all.