Controlling collective tasks with an ALN

摘要

In this paper, the authors explore the idea of using an adaptive logic network (ALN) for behavior arbitration. Their approach is to define the collective task, to be performed by multiple robots, as a group behavior. The group behavior is a set of behaviors, each of which specifies a single step in the collective task. An environmental cue can be used to control the transition between behaviors, thus allowing the progress of the collective task to self-govern its execution. The authors simplify the behavior arbitration in the collective task by training an ALN implemented using simple combinational logic. They provide a description of the Collective Robotic Intelligence Project (CRIP) including the simulation results and the multi-robot system on which these results will be deployed.