Linear Programming Approach to Deceptive Path Planning Game with Goal Selection
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arXiv
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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2026
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| _version_ | 1866911690432446464 |
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| author | Rostobaya, Violetta Guan, Yue Berneburg, James Shishika, Daigo |
| author_facet | Rostobaya, Violetta Guan, Yue Berneburg, James Shishika, Daigo |
| contents | In adversarial settings, a mobile agent may strategically plan its motion to influence an opponent's inference about its intended goal. We study deceptive path planning in a scenario where a mobile agent aims to reach a privately selected goal while an adversarial observer allocates limited defensive resources based on the observed trajectory. Unlike classical path-planning and goal-recognition approaches that model observers as passive inference process, our game-theoretic formulation models them as strategic decision-makers. For the resulting dynamic asymmetric-information game, we develop an efficient solution method that combines a linear programming formulation with the Double Oracle algorithm. To evaluate performance, we introduce metrics that quantify both the risk and the effectiveness of deception and provide illustrative numerical examples. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2605_16548 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Linear Programming Approach to Deceptive Path Planning Game with Goal Selection Rostobaya, Violetta Guan, Yue Berneburg, James Shishika, Daigo Systems and Control In adversarial settings, a mobile agent may strategically plan its motion to influence an opponent's inference about its intended goal. We study deceptive path planning in a scenario where a mobile agent aims to reach a privately selected goal while an adversarial observer allocates limited defensive resources based on the observed trajectory. Unlike classical path-planning and goal-recognition approaches that model observers as passive inference process, our game-theoretic formulation models them as strategic decision-makers. For the resulting dynamic asymmetric-information game, we develop an efficient solution method that combines a linear programming formulation with the Double Oracle algorithm. To evaluate performance, we introduce metrics that quantify both the risk and the effectiveness of deception and provide illustrative numerical examples. |
| title | Linear Programming Approach to Deceptive Path Planning Game with Goal Selection |
| topic | Systems and Control |
| url | https://arxiv.org/abs/2605.16548 |