Autonomous nondeterministic tour guides: improving quality of experience with TTD-MDPs

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. Categories and Subject Descriptors I.2.11 [Artificial Intelligence]: Distributed Artificial Intelligence— Intelligent agents; G.3 [Probability and Statistics]: Markov processes General Terms Algorithms, Measurement, Design Keywords Markov decision processes, interactive entertainment

• Type: Conference
• Year: 2007
• Where: ATAL
• Authors: Andrew S. Cantino, David L. Roberts, Charles L. Isbell
• Keywords: ATAL 2007, Autonomous Agents, Intelligence— Intelligent Agents, Keywords Markov Decision