Fairness in Multi-Agent Planning
- URL: http://arxiv.org/abs/2212.00506v2
- Date: Mon, 22 May 2023 10:55:25 GMT
- Title: Fairness in Multi-Agent Planning
- Authors: Alberto Pozanco, Daniel Borrajo
- Abstract summary: This paper adapts well-known fairness schemes to Multi-Agent Planning (MAP)
It introduces two novel approaches to generate cost-aware fair plans.
Empirical results in several standard MAP benchmarks show that these approaches outperform different baselines.
- Score: 2.7184224088243356
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: In cooperative Multi-Agent Planning (MAP), a set of goals has to be achieved
by a set of agents. Independently of whether they perform a pre-assignment of
goals to agents or they directly search for a solution without any goal
assignment, most previous works did not focus on a fair
distribution/achievement of goals by agents. This paper adapts well-known
fairness schemes to MAP, and introduces two novel approaches to generate
cost-aware fair plans. The first one solves an optimization problem to
pre-assign goals to agents, and then solves a centralized MAP task using that
assignment. The second one consists of a planning-based compilation that allows
solving the joint problem of goal assignment and planning while taking into
account the given fairness scheme. Empirical results in several standard MAP
benchmarks show that these approaches outperform different baselines. They also
show that there is no need to sacrifice much plan cost to generate fair plans.
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