Using geometric diffusions for recognition-primed multi-agent decision making

Several areas of multi-agent research, such as large-scale agent organization and experience-based decision making, demand novel perspectives and efficient approaches for multiscale information analysis. A recent breakthrough in harmonic analysis is diffusion geometry and diffusion wavelets, which offers a general framework for multiscale analysis of massive data sets. In this paper, we introduce the "diffusion"concept into the MAS field, and investigate the impacts of using diffusion distance on the performance of solution synthesis in experience-based multi-agent decision making. In particular, we take a two-dimensional perspective to explore the use of diffusion distance and Euclidean distance in identifying `similar' experiences

• Type: Conference
• Year: 2010
• Where: ATAL
• Authors: Xiaocong Fan, Meng Su
• Keywords: ATAL 2010, Decision Making, Diffusion Distance, Intelligent Agents, Multi-agent Decision Making