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2010
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Intelligent online case-based planning agent model for real-time strategy games

9 years 8 months ago
Intelligent online case-based planning agent model for real-time strategy games
Research in learning and planning in real-time strategy (RTS) games is very interesting in several industries such as military industry, robotics, and most importantly game industry. A recent published work on online case-based planning in RTS Games does not include the capability of online learning from experience, so the knowledge certainty remains constant, which leads to inefficient decisions. In this paper, an intelligent agent model based on both online casebased planning (OLCBP) and reinforcement learning (RL) techniques is proposed. In addition, the proposed model has been evaluated using empirical simulation on Wargus (an open-source clone of the well known RTS game Warcraft 2). This evaluation shows that the proposed model increases the certainty of the case base by learning from experience, and hence the process of decision making for selecting more efficient, effective and successful plans. Keywords- Case-based Reasoning; Reinforcement Learning; Online Case-based Planning; ...
Ibrahim Fathy, Mostafa Aref, Omar Enayet, Abdelrah
Added 13 Feb 2011
Updated 13 Feb 2011
Type Journal
Year 2010
Where ISDA
Authors Ibrahim Fathy, Mostafa Aref, Omar Enayet, Abdelrahman Al-Ogail
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