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首页> 外文会议>World multi-conference on systemics, cybernetics and informatics;WMSCI 2008;ISAS;International conference on Information systems analysis and synthesis >G-Bots: Intelligent Agents in a Complex Simulated Environment
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G-Bots: Intelligent Agents in a Complex Simulated Environment

机译：G-bot：复杂模拟环境中的智能代理

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摘要

The G-Bots project focuses on the development of an intelligent agent-based architecture for a real-time simulated environment. The agent architecture interacts with a Newtonian physics-based environment, given a set of sensors and actuators. The environment consists of small circular planets and other objects in two-dimensional space. In each game episode, each intelligent agent must try to eliminate the others by causing objects, such as rocks, to hit them, while minimizing hits to itself. After receiving a certain number of hits, an agent is eliminated from the episode. An agent can perform actions such as driving on a planet's surface, picking up an object, throwing an object, and launching itself at a given angle and velocity. The planets exert conflicting gravitational pulls that the agents must account for in their predictions of object motion. Artificial neural networks (ANNs) will be used to improve the agents' performance, including better aiming accuracy and trajectory prediction.
机译：G-Bots项目专注于为实时模拟环境开发基于智能代理的体系结构。给定一组传感器和执行器，该代理架构与基于牛顿物理学的环境进行交互。环境由二维空间中的小圆形行星和其他物体组成。在每个游戏情节中，每个智能代理必须设法通过使诸如岩石之类的物体撞击它们来消除其他物体，同时使对自身的撞击最小化。收到一定数量的点击后，特工将从该剧集中被淘汰。特工可以执行诸如在行星表面上行驶，捡起物体，投掷物体以及以给定的角度和速度发射自身的动作。行星施加了相互矛盾的引力，这些引力必须由代理商在预测物体运动时加以考虑。人工神经网络（ANN）将用于改善特工的性能，包括更好的瞄准精度和轨迹预测。

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