Resource Allocation with Multi-Team Collaboration Based on Hamilton's Rule

TL;DR

This paper introduces a multi-team resource allocation strategy inspired by ecological Hamilton's rule, optimizing agent sharing among teams for coverage missions.

Contribution

It develops an algorithmic framework for multi-team resource sharing based on Hamilton's rule, considering costs, benefits, and mission importance.

Findings

Framework effectively allocates resources among teams in simulations.

Mission evaluation function based on coverage cost meets necessary criteria.

Algorithm improves multi-team collaboration efficiency.

Abstract

This paper presents a multi-team collaboration strategy based on Hamilton's rule from ecology that facilitates resource allocation among multiple teams, where agents are considered as shared resource among all teams that must be allocated appropriately. We construct an algorithmic framework that allows teams to make bids for agents that consider the costs and benefits of transferring agents while also considering relative mission importance for each team. This framework is applied to a multi-team coverage control mission to demonstrate its effectiveness. It is shown that the necessary criteria of a mission evaluation function are met by framing it as a function of the locational coverage cost of each team with respect to agent gain and loss, and these results are illustrated through simulations.