Anti-interception guidance for hypersonic glide vehicle: a deep reinforcement learning approach

L Jiang, Y Nan, Y Zhang, Z Li - Aerospace, 2022 - mdpi.com
Anti-interception guidance can enhance a hypersonic glide vehicle (HGV) compard to
multiple interceptors. In general, anti-interception guidance for aircraft can be divided into …

SwarmBrain: Embodied agent for real-time strategy game StarCraft II via large language models

X Shao, W Jiang, F Zuo, M Liu - arxiv preprint arxiv:2401.17749, 2024 - arxiv.org
Large language models (LLMs) have recently garnered significant accomplishments in
various exploratory tasks, even surpassing the performance of traditional reinforcement …

A new approach to solving smac task: Generating decision tree code from large language models

Y Deng, W Ma, Y Fan, Y Zhang, H Zhang… - arxiv preprint arxiv …, 2024 - arxiv.org
StarCraft Multi-Agent Challenge (SMAC) is one of the most commonly used experimental
environments in multi-agent reinforcement learning (MARL), where the specific task is to …

Orchestrating and Scheduling System for Workflows in Heterogeneous and Dynamic Environment

W Liang, H Lin, H Shen, E Wang - IEEE INFOCOM 2024-IEEE …, 2024 - ieeexplore.ieee.org
Many Orchestrating and scheduling systems and algorithms have been proposed or
deployed in Cloud computing and Edge computing scenarios, where computing resources …

An Efficient Multi-Agent Policy Self-Play Learning Method Aiming at Seize-Control Scenarios

H Zhang, H Ma, X Zhang, L Wang, M Han… - Unmanned …, 2024 - shibata.yubetsu.com
An Efficient Multi-Agent Policy Self-Play Learning Method Aiming at Seize-Control Scenarios -
Yubetsu Shibata Yubetsu Shibata logo About Browse For Publishers Contact 1.Unmanned …

Revisiting of AlphaStar

RZ Liu, Y Shen, Y Yu - IEEE Transactions on Games, 2023 - ieeexplore.ieee.org
Research on StarCraft II (SC2) is considered important due to its similarity to real-life tasks
and its potential to inspire game artificial intelligence design. However, the complexity of …

[CITATION][C] Adaptive Command: Real-Time Policy Adjustment via Language Models in StarCraft II

W Ma, D Xu, S Lin, H Zhang, J Wang