Initial Goal Allocation for Multi-agent Systems

Abstract

In the multi-agent environment, a human expert engages in
the allocation of objectives among individual agents. How-
ever, autonomous agents need to determine and allocate ob-
jectives without external intervention from humans. There-
fore, in this research, we attempt to solve initial goal distri-
bution challenges in multi-agent settings by developing two
goal allocation algorithms. The primary objectives are to find
cost-effective goal solution sets and distribute them evenly
among available agents. We introduce two algorithms when
the goals are structured in a hierarchical goal tree structure,
and then test their efficiency across a variety of baseline al-
location methods. Both algorithms were able to increase the
performance of agents in multi-agent settings by finding the
most optimal distributions of goals and allowing agents to act
independently from human intervention.

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