Search for a moving target in a competitive environment

Competitive Search in a Network

We study the classic problem in which a Searcher must locate a hidden point, also called the Hider in a network, starting from a root point. The network may be either bounded or unbounded, thus generalizing well-known settings such as linear and star search. We distinguish between pathwise search, in which the Searcher follows a continuous unit-speed path until the Hider is reached, and expanding search, in which, at any point in time, the Searcher may restart from any previously reached point. The former has been the usual paradigm for studying search games, whereas the latter is a more recen…

两站点移动目标搜索的Ross猜想的一个证明

A proof of Ross's conjecture for two-site moving-target search

针对两站点移动目标搜索问题，在MacPhee和Jordan部分证明的基础上，完整证明了Ross猜想在整个正行列式参数区域成立，解决了该猜想的剩余情况。

带移动障碍物的移动目标旅行商问题的两阶段双层搜索

Two-Phase Bilevel Search for the Moving-Target Traveling Salesman Problem with Moving Obstacles

针对带移动障碍物的移动目标旅行商问题，提出混合整数锥规划公式和两阶段双层搜索算法，显著优于基线方法。

针对运动并伪装目标的多智能体搜索

Multi-Agent Search for a Moving and Camouflaging Target

本文研究异构多智能体搜索随机运动伪装目标的规划问题，将凸混合整数非线性规划线性化，并结合预处理、惰性约束和基于束的割平面方法提升大规模求解效率。

竞争性品类规划算法模型

A Model of Competitive Assortment Planning Algorithm

本文构建融合贝叶斯信息更新与两阶段优化的竞争性品类规划算法模型，刻画平台、供应商和自有品牌间的竞争与合谋，并提出无合谋且能最大化期望收益的方案。

Simple random search provides a competitive approach to reinforcement learning

A common belief in model-free reinforcement learning is that methods based on random search in the parameter space of policies exhibit significantly worse sample complexity than those that explore the space of actions. We dispel such beliefs by introducing a random search method for training static, linear policies for continuous control problems, matching state-of-the-art sample efficiency on the benchmark MuJoCo locomotion tasks. Our method also finds a nearly optimal controller for a challenging instance of the Linear Quadratic Regulator, a classical problem in control theory, when the dyna…