Case Acquisition Strategies for Case-Based Reasoning in Real-Time Strategy Games

Real-time Strategy (RTS) games are complex domains which are a significant challenge to both human and artificial intelligence (AI). For that reason, and although many AI approaches have been proposed for the RTS game AI problem, the AI of all commercial RTS games is scripted and offers a very static behavior subject to exploits. In this paper, we will focus on a case-based reasoning (CBR) approach to this problem, and concentrate on the process of case-acquisition. Specifically, we will describe 7 different techniques to automatically acquire plans by observing human demonstrations and compare their performance when using them in the Darmok 2 system in the context of an RTS game.

[1]  Ashwin Ram,et al.  Transfer Learning in Real-Time Strategy Games Using Hybrid CBR/RL , 2007, IJCAI.

[2]  Santiago Onta,et al.  Learning from Human Demonstrations for Real-Time Case-Based Planning , 2009 .

[3]  Brett Browning,et al.  A survey of robot learning from demonstration , 2009, Robotics Auton. Syst..

[4]  Michael Mateas,et al.  A data mining approach to strategy prediction , 2009, 2009 IEEE Symposium on Computational Intelligence and Games.

[5]  John E. Laird,et al.  Learning Goal Hierarchies from Structured Observations and Expert Annotations , 2004, ILP.

[6]  Michael Buro,et al.  Real-Time Strategy Games: A New AI Research Challenge , 2003, IJCAI.

[7]  Santiago Ontañón.  Towards a Unified Framework for Learning from Observation , 2011 .

[8]  Bhaskara Marthi,et al.  Concurrent Hierarchical Reinforcement Learning , 2005, IJCAI.

[9]  Jonathan Schaeffer,et al.  Monte Carlo Planning in RTS Games , 2005, CIG.

[10]  Michael Mateas,et al.  An Integrated Agent for Playing Real-Time Strategy Games , 2008, AAAI.

[11]  David W. Aha,et al.  Learning to Win: Case-Based Plan Selection in a Real-Time Strategy Game , 2005, Künstliche Intell..

[12]  Tadao Murata,et al.  Petri nets: Properties, analysis and applications , 1989, Proc. IEEE.

[13]  Babak Esfandiari,et al.  Learning state-based behaviour using temporally related cases , 2011 .

[14]  Santiago Ontañón,et al.  On-Line Case-Based Plan Adaptation for Real-Time Strategy Games , 2008, AAAI.

[15]  Hector Muñoz-Avila,et al.  HTN-MAKER: Learning HTNs with Minimal Additional Knowledge Engineering Required , 2008, AAAI.

[16]  Babak Esfandiari,et al.  A Case-Based Reasoning Approach to Imitating RoboCup Players , 2008, FLAIRS.

[17]  Santiago Ontañón,et al.  ON‐LINE CASE‐BASED PLANNING , 2010, Comput. Intell..