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arXiv · 2510.04050

A Dynamic Programming Approach to Evader Pathfinding in Static Pursuit Scenarios

Sukanya Samanta·Manohar Reddy
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Abstract

The interdiction of escaping adversaries in urban networks is a critical security challenge. State-of-the-art game-theoretic models, such as the Escape Interdiction Game (EIG), provide comprehensive frameworks but assume a highly dynamic interaction and entail significant computational complexity, which can be prohibitive for real-time applications. This paper investigates a crucial sub-problem: an evader's optimal pathfinding calculus when faced with a static or pre-determined defender deployment. We propose the Dynamic Programming for Evader Route Optimization (DPERO) algorithm, which models the environment as a graph with probabilistic risks at various nodes. By transforming the multiplicative survival objective into an additive cost function using logarithms, we frame the task as a shortest path problem solvable with value iteration. This approach allows for the efficient computation of a path that optimally balances safety and distance. Experimental results on simulated grid networks demonstrate that DPERO identifies routes with significantly higher survival probabilities compared to naive shortest-path baselines, validating its efficacy as a practical tool for vulnerability analysis and strategic planning.

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Sukanya Samanta, Manohar Reddy. 2025-10-05. A Dynamic Programming Approach to Evader Pathfinding in Static Pursuit Scenarios. https://arxiv.org/abs/2510.04050

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