2011/03/25 by Vadas Gintautas, Gintautas, Vadas, Aric Hagberg +4
Computer Science · Decision Sciences · Mathematics · #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Game Theory and Applications #Information Theory (cs.IT) #Metaheuristic Optimization Algorithms Research #Optimization and Search Problems #cs.AI #cs.IT #math.IT
paper · pdf · doi:10.48550/arxiv.1103.4888
Journal of Intelligence Community Research and Development, permanently available on Intelink, October 2010
arxiv created 2011/03/25 · openalex publication_date 2011/03/25 · arxiv updated 2011/03/28 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Spatial search problems abound in the real world, from locating hidden nuclear or chemical sources to finding skiers after an avalanche. We exemplify the formalism and solution for spatial searches involving two agents that may or may not choose to share information during a search. For certain classes of tasks, sharing information between multiple searchers makes cooperative searching advantageous. In some examples, agents are able to realize synergy by aggregating information and moving based on local judgments about maximal information gathering expectations. We also explore one- and two-dimensional simplified situations analytically and numerically to provide a framework for analyzing more complex problems. These general considerations provide a guide for designing optimal algorithms for real-world search problems.