AI RESEARCH
Repeated Deceptive Path Planning against Learnable Observer
arXiv CS.AI
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ArXi:2605.07174v1 Announce Type: new We study the problem of deceptive path planning (DPP), where an agent aims to conceal its true destination from external observers. While existing work assumes static, non-learning observers, real-world adversaries-such as in critical goods transportation or military operations-can adapt by learning from historical trajectories. To address this gap, we