Deep Reinforcement Learning (DRL) is poised to revolutionize the field of AI and represents a step towards general intelligence. Currently, AlphaStar achieved the Grandmaster level in StarCraft gaming, which is a remarkable breakthrough in Real-Time Strategy (RTS) gaming. The paper discusses the general framework of RTS gaming agents, and presents the method innovation from baseline RL algorithms to the AlphaStar. We begin with the basic idea and taxonomy of DRL, then progress to the technical framework of AlphaStar from the perspective of state space design, action space design, policy and value net framework and multi-agent training methods, presenting key issue and feasible method in full-length scale of RTS gaming. Finally, we draw a brief conclusion.
Intention recognition of air target formations plays a crucial role in modern air warfare. Therefore, the paper combines expert experience and domain knowledge to propose a formation intention determination method based on a thermal grid map. Firstly, the confrontation area is reasonably gridded, secondly, a thermal distribution grid map is generated based on the spatial characteristics of the target intelligence data, then formations are derived based on the map, and finally the intention of each formation is judged based on the adversarial rules. In order to evaluate the feasibility of this method, a data case is given in this paper to demonstrate its effectiveness in practical application.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.