Punctuated Anytime Learning for Autonomous Agent Control

2015 ◽  
pp. 89-107
Author(s):  
Gary Parker
Keyword(s):  
Autonomous Agent ◽  
Agent Control ◽  
Anytime Learning

Learning Control for an Xpilot-AI Agent Playing Capture the Flag

2012 ◽  
Vol 3 (1) ◽  
pp. 1-12
Author(s):  
Gary Parker ◽  
Sarah Penrose
Keyword(s):  
Genetic Algorithm ◽  
Open Source ◽  
Learning Control ◽  
Autonomous Agent ◽  
Challenging Problem ◽  
Wide Range ◽  
Learning Programs ◽  
Agent Control ◽  
2D Space

Xpilot-AI is an environment where researchers can test autonomous agent control and learning programs. It is based on Xpilot, which is an open source, 2d space combat game. Xpilot-AI allows a programmer to write scripts that control an agent playing a game of Xpilot. In previous work, a wide range of techniques have been used to develop controllers that are focused on the combat skills for an Xpilot agent. In this research, a Genetic Algorithm (GA) was used to evolve the parameters for an expert agent solving the more challenging problem of capture the flag.

Multi-agent Control of Customer^|^apos;s Loads for Influence of Renewable Energy on the Power System

2014 ◽  
Vol 134 (10) ◽  
pp. 1515-1523
Author(s):  
Akihiro Ogawa ◽  
Kazunari Maki ◽  
Kiyoshi Hata ◽  
Yasunori Takeuchi ◽  
Fumio Ishikawa
Keyword(s):  
Renewable Energy ◽  
Power System ◽  
Multi Agent ◽  
Agent Control
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