Contested Route Planning

2025-08-13

AI Summary

In adversarial environments, logistics routes are highly vulnerable to disruption, and conventional deterministic path planning methods suffer from poor predictability and low mission survivability. Method: This paper proposes a randomized path planning framework based on a two-player zero-sum game. To overcome the limitations of deterministic approaches, we introduce a dual-Oracle game architecture: one Oracle encapsulates a specialized path-planning algorithm, while the other models the adversary’s capabilities; together, they jointly optimize attacker behavior and defensive routing strategies. The framework explicitly incorporates attacker capabilities and generates diverse, unpredictable route distributions. Contribution/Results: The method achieves high computational efficiency—solutions are computed in seconds—while significantly improving mission success rates and vehicle survivability. Empirical evaluation on realistic scenarios demonstrates substantial improvements in protection effectiveness over baseline methods, confirming its practical deployability and scalability to large-scale operations.

Technology Category

• Planning, Routing, and Scheduling: Planning with Language Models
• Search and Optimization: Adversarial Search
• Multiagent Systems: Adversarial Agents

Application Category

• User Modeling, Personalization and Recommendation: Attacks and countermeasures in recommendation systems
• Security and Privacy: Large-scale security measurements
• Economics, Online Markets and Human Computation: Uses of LLMs and GenAI for marketplace design, bidding, and strategic interactions

Abstract

We consider the problem of routing for logistics purposes, in a contested environment where an adversary attempts to disrupt the vehicle along the chosen route. We construct a game-theoretic model that captures the problem of optimal routing in such an environment. While basic robust deterministic routing plans are already challenging to devise, they tend to be predictable, which can limit their effectiveness. By introducing calculated randomness via modeling the route planning process as a two-player zero-sum game, we compute immediately deployable plans that are diversified and harder to anticipate. Although solving the game exactly is intractable in theory, our use of the double-oracle framework enables us to achieve computation times on the order of seconds, making the approach operationally viable. In particular, the framework is modular enough to accommodate specialized routing algorithms as oracles. We evaluate our method on real-world scenarios, showing that it scales effectively to realistic problem sizes and significantly benefits from explicitly modeling the adversary's capabilities, as demonstrated through ablation studies and comparisons with baseline approaches.

Problem

• Optimal routing in contested adversarial environments
• Game-theoretic model for unpredictable route planning
• Scalable double-oracle framework for real-world logistics

Innovation

• Game-theoretic model for contested routing
• Double-oracle framework for fast computation
• Modular design with specialized routing algorithms