Fuzzy case-based reasoning for managing strategic and tactical reasoning in starcraft

Authors:
Pedro Cadena;Leonardo Garrido
Affiliations:
Tecnológico de Monterrey, Monterrey, Nuevo León, México;Tecnológico de Monterrey, Monterrey, Nuevo León, México
Venue:
MICAI'11 Proceedings of the 10th Mexican international conference on Advances in Artificial Intelligence - Volume Part I
Year:
2011

Citing 5
Cited 0

Case-based reasoning: foundational issues, methodological variations, and system approaches

AI Communications
Case-Based Planning and Execution for Real-Time Strategy Games

ICCBR '07 Proceedings of the 7th international conference on Case-Based Reasoning: Case-Based Reasoning Research and Development
An integrated agent for playing real-time strategy games

AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 3
Artificial Intelligence: A Modern Approach

Artificial Intelligence: A Modern Approach
Learning to win: case-based plan selection in a real-time strategy game

ICCBR'05 Proceedings of the 6th international conference on Case-Based Reasoning Research and Development

Quantified Score

Hi-index	0.00

Visualization

Abstract

We present the combination of Fuzzy sets and Case-Based Reasoning (FCBR) to deal with strategic and tactical management in the real-time strategy environment of StarCraft. Case-based reasoning is a problem solving AI approach that uses past experience to deal with actual problems. Fuzzy set theory is used in case representation to provide a characterization of imprecise and uncertain information. The results revealed that our system can successfully reason about strategies and tactics, defeating the built-in AI of StarCraft. The principal conclusion was that FCBR can reason with abstract information and a large space of actions. Moreover, the resulting system shows its potential to incorporate human knowledge and can effectively adapt to varying conditions of the map.