Coverage Games

2026-03-20

AI Summary

This work addresses the challenge of guaranteeing that all objectives are satisfied by at least one agent in multi-agent systems where full control over every agent is unattainable. To this end, the paper introduces the “coverage game” framework, which models an adversarial interaction between a covering team—collaboratively striving to fulfill all objectives—and an interfering adversary aiming to block them. This framework extends multi-objective games to a multi-agent setting with dynamic objective assignment, integrating formal game theory, multi-agent planning, and automata theory for systematic analysis. The main contributions include a complete characterization of the decision complexity of coverage games, solutions to the winnability problems for both players, and the development of efficient algorithms under restricted settings such as single-player games or a fixed number of agents.

Technology Category

• Multiagent Systems: Adversarial Agents
• Game Theory and Economic Paradigms: Adversarial Learning
• Search and Optimization: Adversarial Search

Application Category

• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems
• Graph Algorithms and Modeling for the Web: Algorithms and analysis for incomplete, noisy, or partially observed Web-related graphs
• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications

Abstract

We introduce and study coverage games - a novel framework for multi-agent planning in settings in which a system operates several agents but does not have full control on them, or interacts with an environment that consists of several agents. The game is played between a coverer, who has a set of objectives, and a disruptor. The coverer operates several agents that interact with the adversarial disruptor. The coverer wins if every objective is satisfied by at least one agent. Otherwise, the disruptor wins. Coverage games thus extend traditional two-player games with multiple objectives by allowing a (possibly dynamic) decomposition of the objectives among the different agents. They have many applications, both in settings where the system is the coverer (e.g., multi-robot surveillance, coverage in multi-threaded systems) and settings where it is the disruptor (e.g., prevention of resource exhaustion, ensuring non-congestion). We first study the theoretical properties of coverage games, including determinacy, and the ability to a priori decompose the objectives among the agents. We then study the problems of deciding whether the coverer or the disruptor wins. Besides a comprehensive analysis of the tight complexity of the problems, we consider interesting special cases, such as the one-player cases and settings with a fixed number of agents or objectives.

Problem

• coverage games
• multi-agent planning
• adversarial environment
• objective coverage
• two-player games

Innovation

• coverage games
• multi-agent planning
• objective decomposition
• adversarial interaction
• game determinacy