{"ID":2860213,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2510.04050","arxiv_id":"2510.04050","title":"A Dynamic Programming Approach to Evader Pathfinding in Static Pursuit Scenarios","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.","short_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 prohibit...","url_abs":"https://arxiv.org/abs/2510.04050","url_pdf":"https://arxiv.org/pdf/2510.04050v1","authors":"[\"Sukanya Samanta\",\"Manohar Reddy\"]","published":"2025-10-05T06:12:42Z","proceeding":"cs.DS","tasks":"[\"cs.DS\"]","methods":"[]","has_code":false}