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arXiv research

A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.

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6 results for “Pursuit-Evasion”

Thompson Sampling for Pursuit-Evasion Problemscs.LG

Thompson Sampling improves pursuit-evasion coordination.

problem Optimizing pursuer behavior to capture an evader efficiently.

method Variant of Thompson Sampling applied to pursuit-evasion problems.

result Thompson Sampling reduces time-to-capture significantly.

Thompson Sampling Pursuit-Evasion Defense Route Planning Model-Based Planning

2018-11-11abs ↗pdf ↗

Pursuit-Evasion on a Sphere and When It Can Be Considered Flatmath.OC

Study of pursuit-evasion game on sphere and its relation to planar Apollonius circle.

problem Analyzing pursuit-evasion game on a sphere and its properties.

method Extending classical planar pursuit-evasion game to spherical geometry, studying equilibrium intercept points and their relation to Apollonius domain.

result Condition for intercept point to belong to Apollonius domain on sphere, analogous to planar game.

pursuit-evasion sphere Apollonius domain equilibrium strategies numerical simulations

2024-03-22abs ↗pdf ↗

A Generative Machine Learning Approach to Policy Optimization in Pursuit-Evasion Gamescs.LG

Generative ML learns optimal pursuit trajectories in pursuit-evasion games.

problem Optimizing Blue's pursuit trajectory to intercept Red in a game of pursuit-evasion.

method Applying generative machine learning to learn optimal action policies for Blue.

result Generative ML models can learn relevant representations for pursuit-evasion dynamics.

pursuit-evasion policy optimization machine learning generative models sequential decision making

2020-10-04abs ↗pdf ↗

On Solving the 2-Dimensional Greedy Shooter Problem for UAVscs.RO

UAVs use RL to outperform a greedy shooter in 2D engagements.

problem Optimizing UAV pursuit-evasion strategies in 2D environments.

method Reinforcement learning applied to a greedy shooter strategy in a 2D aerial engagement.

result Deep Q-learning UAV outperforms greedy shooter UAV in simulations.

UAVs reinforcement learning greedy shooter 2D engagement retrieval

2019-11-02abs ↗pdf ↗

Brachistochrone Pursuit - Evasion Games and Riemann-Finsler Geometrymath.OC

A geometric approach to differential game theory is illustrated. The parallel pursuit is considered as a two-player zero-sum differential game. The optimal strategies of each player is designed based on Riemann-Finsler geometry. Our approach incorporates a closed loop optimal control and the presentation is familiar wi…

2011-01-10abs ↗pdf ↗

Deep Reinforcement Learning for Swarm Systemscs.MA

Recently, deep reinforcement learning (RL) methods have been applied successfully to multi-agent scenarios. Typically, these methods rely on a concatenation of agent states to represent the information content required for decentralized decision making. However, concatenation scales poorly to swarm systems with a large…

2018-07-17abs ↗pdf ↗