Interfacing Agents to Real-Time Strategy Games

نویسندگان

  • Andreas Schmidt Jensen
  • Christian Kaysø-Rørdam
  • Jørgen Villadsen
چکیده

In real-time strategy games players make decisions and control their units simultaneously. Players are required to make decisions under time pressure and should be able to control multiple units at once in order to be successful. We present the design and implementation of a multi-agent interface for the real-time strategy game STARCRAFT: BROOD WAR. This makes it possible to build agents that control each of the units in a game. We make use of the Environment Interface Standard, thus enabling different agent programming languages to use our interface, and we show how agents can control the units in the game in the Jason and GOAL agent programming languages.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Robust Opponent Modeling in Real-Time Strategy Games using Bayesian Networks

Opponent modeling is a key challenge in Real-Time Strategy (RTS) games as the environment is adversarial in these games, and the player cannot predict the future actions of her opponent. Additionally, the environment is partially observable due to the fog of war. In this paper, we propose an opponent model which is robust to the observation noise existing due to the fog of war. In order to cope...

متن کامل

SORTS: A Human-Level Approach to Real-Time Strategy AI

We developed knowledge-rich agents to play real-time strategy games by interfacing the ORTS game engine to the Soar cognitive architecture. The middleware we developed supports grouping, attention, coordinated path finding, and FSM control of low-level unit behaviors. The middleware attempts to provide information humans use to reason about RTS games, and facilitates creating agent behaviors in...

متن کامل

Automated terrain analysis in real-time strategy games

Real-time strategy (RTS) games represent a mainstream genre of video games. They are also practical test-beds for intelligent agents, which have received considerable interest from Artificial Intelligence (AI) researchers, in particular game AI researchers. Terrain knowledge understanding is a fundamental issue for RTS agents and map decomposition methods can help AI agents in representing terr...

متن کامل

Modeling Unit Classes as Agents in Real-Time Strategy Games

We present CLASSQL, a multi-agent model for playing real-time strategy games, where learning and control of our own team’s units is decentralized; each agent uses its own reinforcement learning process to learn and control units of the same class. Coordination between these agents occurs as a result of a common reward function shared by all agents and synergistic relations in a carefully crafte...

متن کامل

Incorporating Search Algorithms into RTS Game Agents

Real-time strategy (RTS) games are known to be one of the most complex game genres for humans to play, as well as one of the most difficult games for computer AI agents to play well. To tackle the task of applying AI to RTS games, recent techniques have focused on a divide-and-conquer approach, splitting the game into strategic components, and developing separate systems to solve each. This tre...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2015