Abstract: This 1 paper 2 solves an enhanced adaptive dynamic programming (ADP)-based collision-free enclosing learning control for Unmanned Aerial Vehicles (UAVs) to move around a specified target ...

Abstract: In this paper, the novel prescribed-time dynamic event-triggered control method of an unknown multiplayer nonzero-sum game (MP-NZSG) is designed by using adaptive dynamic programming (ADP).

The prospect of increased U.S. influence over Venezuela's oil industry is raising questions about Washington's potential future role in OPEC, the cartel of global oil producers that President Trump ...

For much of the last half century, static efficiency has been posited to be in tension with dynamic efficiency. Theorists such as Schumpeter and Williamson introduced models suggesting that firms ...

Currently, the LMS Question module restricts multiple-choice questions to a fixed number of options This limitation makes it difficult to create questions that require more than four distractors, ...

Royalty-free licenses let you pay once to use copyrighted images and video clips in personal and commercial projects on an ongoing basis without requiring additional payments each time you use that ...

This study develops a unified framework for optimal portfolio selection in jump–uncertain stochastic markets, contributing both theoretical foundations and computational insights. We establish the ...

The president of the arts center cited the TV show “So You Think You Can Dance” as the type of programming that could be more broadly appealing to audiences. By Julia Jacobs The John F. Kennedy Center ...

ABSTRACT: To provide quantitative analysis of strategic confrontation game such as cross-border trades like tariff disputes and competitive scenarios like auction bidding, we propose an alternating ...

State Key Laboratory of Extreme Photonics and Instrumentation, Zhejiang Key Laboratory of Excited-State Energy Conversion and Energy Storage, Department of Chemistry, Zhejiang University, Hangzhou, ...

ABSTRACT: Offline reinforcement learning (RL) focuses on learning policies using static datasets without further exploration. With the introduction of distributional reinforcement learning into ...