Synthesis of Cost-Optimal Multi-Agent Systems for Resource Allocation

TL;DR

This paper introduces a method to synthesize cost-optimal strategies for multi-agent systems in resource allocation, ensuring goal achievement with minimal resource costs using Max-SAT solving techniques.

Contribution

It presents a novel approach that reduces the synthesis of cost-optimal strategies to a Max-SAT problem, enabling efficient automated solution generation.

Findings

The approach successfully synthesizes cost-minimal strategies.

It guarantees goal achievement with optimized resource costs.

The method leverages propositional logic encoding and Max-SAT solvers.

Abstract

Multi-agent systems for resource allocation (MRAs) have been introduced as a concept for modelling competitive resource allocation problems in distributed computing. An MRA is composed of a set of agents and a set of resources. Each agent has goals in terms of allocating certain resources. For MRAs it is typically of importance that they are designed in a way such that there exists a strategy that guarantees that all agents will achieve their goals. The corresponding model checking problem is to determine whether such a winning strategy exists or not, and the synthesis problem is to actually build the strategy. While winning strategies ensure that all goals will be achieved, following such strategies does not necessarily involve an optimal use of resources. In this paper, we present a technique that allows to synthesise cost-optimal solutions to distributed resource allocation problems. We consider a scenario where system components such as agents and resources involve costs. A multi-agent system shall be designed that is cost-minimal but still capable of accomplishing a given set of goals. Our approach synthesises a winning strategy that minimises the cumulative costs of the components that are required for achieving the goals. The technique is based on a propositional logic encoding and a reduction of the synthesis problem to the maximum satisfiability problem (Max-SAT). Hence, a Max-SAT solver can be used to perform the synthesis. From a truth assignment that maximises the number of satisfied clauses of the encoding a cost-optimal winning strategy as well as a cost-optimal system can be immediately derived.