Retrieving and Reusing Game Plays for Robot Soccer

The problem of defining robot behaviors to completely address a large and complex set of situations is very challenging. We present an approach for robot's action selection in the robot soccer domain using Case-Based Reasoning techniques. A case represents a snapshot of the game at time t and the actions the robot should perform in that situation. We basically focus our work on the retrieval and reuse steps of the system, presenting the similarity functions and a planning process to adapt the current problem to a case. We present first results of the performance of the system under simulation and the analysis of the parameters used in the approach.

[1]  Maarja Kruusmaa.  Global Navigation in Dynamic Environments Using Case-Based Reasoning , 2003, Auton. Robots.

[2]  Steffen Brüggert,et al.  Fault-Tolerant Self Localization by Case-Based Reasoning , 2000, RoboCup.

[3]  Agnar Aamodt,et al.  Case-Based Reasoning: Foundational Issues, Methodological Variations, and System Approaches , 1994, AI Commun..

[4]  Martin A. Riedmiller,et al.  Karlsruhe Brainstormers - A Reinforcement Learning Approach to Robotic Soccer , 2000, RoboCup.

[5]  Ramón López de Mántaras,et al.  A CBR System for Autonomous Robot Navigation , 2005, CCIA.

[6]  Matthew Gillen,et al.  Case-Based Reasoning for Planning and World Modeling in the RoboCup Small Size League , 2003 .

[7]  Abhinav Sarje,et al.  Reinforcement learning of player agents in RoboCup Soccer simulation , 2004, Fourth International Conference on Hybrid Intelligent Systems (HIS'04).

[8]  Mario Lenz,et al.  CBR for Dynamic Situation Assessment in an Agent-Oriented Setting , 1998 .

[9]  Agnar Aamodt,et al.  CASE-BASED REASONING: FOUNDATIONAL ISSUES, METHODOLOGICAL VARIATIONS, AND SYSTEM APPROACHES AICOM - ARTIFICIAL INTELLIGENCE COMMUNICATIONS , 1994 .

[10]  Ronald C. Arkin,et al.  Spatio-temporal case-based reasoning for behavioral selection , 2001, Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation (Cat. No.01CH37164).

[11]  Bernhard Nebel,et al.  Case Based Game Play in the RoboCup Four-Legged League Part I The Theoretical Model , 2003, RoboCup.

[12]  J. Shewchuk,et al.  Geometric Similarity Metrics for Case-Based Reasoning , 1994 .

[13]  Ashwin Ram,et al.  Continuous Case-Based Reasoning , 1997, Artif. Intell..

[14]  Manuela Veloso,et al.  Selecting Heterogeneous Team Players by Case-Based Reasoning: A Case Study in Robotic Soccer Simulation , 2002 .

[15]  Andreas D. Lattner,et al.  Sequential Pattern Mining for Situation and Behavior Prediction in Simulated Robotic Soccer , 2005, RoboCup.

[16]  Karen Zita Haigh,et al.  Route Planning by Analogy , 1995, ICCBR.