Generation of Behavior Trees for Dynamic Agents Based on Market Inspired Task Allocation

Abstract: The possibility of using multiple autonomous agents for completing various tasks has gathered a lot of interest in the last years. Using multiple agents does however come with the problems of choosing how to allocate the tasks and how the intelligence of the individual agents should be designed.  In this thesis a market inspired auction system for task allocation and an approach for generating a behavior tree creating the autonomous behavior using a library of available behaviors will be established. The validity of the proposed approach is demonstrated in simulation and with multiple experiments in a laboratory environment. The result does show that the approach promisingly solves the stated problems.