Case-based learning by observation: preliminary work

Authors:
Glen Robertson;Ian Watson
Affiliations:
University of Auckland, Auckland, New Zealand;University of Auckland, Auckland, New Zealand
Venue:
Proceedings of The 8th Australasian Conference on Interactive Entertainment: Playing the System
Year:
2012

Citing 3
Cited 1

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A Case-Based Reasoning Framework for Developing Agents Using Learning by Observation

ICTAI '11 Proceedings of the 2011 IEEE 23rd International Conference on Tools with Artificial Intelligence

From competition to metacognition: designing diverse, sustainable educational games

Proceedings of the SIGCHI Conference on Human Factors in Computing Systems

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Abstract

In this paper, we present an agent which uses case-based reasoning to play the real-time strategy game StarCraft. Cases are gathered through observation of human actions in particular situations, which are extracted from game log files. Cases are then used by a domain-independent case-based reasoning framework to make in-game actions based on human actions in similar situations. This work aims to demonstrate a method for more easily creating better agents in real-time strategy games.