2010/11/15 by Sergey Tarasenko, Tarasenko, Sergey
Computer Science · #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Multiagent Systems (cs.MA) #Robotics (cs.RO) #cs.AI #cs.MA #cs.RO
paper · pdf · doi:10.48550/arxiv.1011.3397
27 pages, 6 figures, 3 tables
arxiv created 2010/11/15 · arxiv updated 2010/11/16
The Reflexive Game Theory (RGT) has been recently proposed by Vladimir Lefebvre to model behavior of individuals in groups. The goal of this study is to introduce the Inverse task. We consider methods of solution together with practical applications. We present a brief overview of the RGT for easy understanding of the problem. We also develop the schematic representation of the RGT inference algorithms to create the basis for soft- and hardware solutions of the RGT tasks. We propose a unified hierarchy of schemas to represent humans and robots. This hierarchy is considered as a unified framework to solve the entire spectrum of the RGT tasks. We conclude by illustrating how this framework can be applied for modeling of mixed groups of humans and robots. All together this provides the exhaustive solution of the Inverse task and clearly illustrates its role and relationships with other issues considered in the RGT.