A framework for knowledge-based temporal abstraction
Artificial Intelligence
Data preparation for data mining
Data preparation for data mining
It knows what you're going to do: adding anticipation to a Quakebot
Proceedings of the fifth international conference on Autonomous agents
How Qualitative Spatial Reasoning Can Improve Strategy Game AIs
IEEE Intelligent Systems
Human-Level AI's Killer Application: Interactive Computer Games
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
Learning hierarchical task networks by observation
ICML '06 Proceedings of the 23rd international conference on Machine learning
Bayesian Imitation of Human Behavior in Interactive Computer Games
ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 01
Qualitative Physics for Movable Objects in MOUT
ANSS '06 Proceedings of the 39th annual Symposium on Simulation
Data mining with Temporal Abstractions: learning rules from time series
Data Mining and Knowledge Discovery
Know thine enemy: a champion robocup coach agent
AAAI'06 proceedings of the 21st national conference on Artificial intelligence - Volume 2
Robotics and Autonomous Systems
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Interactive computer game logs show the potential for use as replacement for time-consuming supervisory learning processes for embodied, situated agents. However, due to the inherent nature of the data in the logs themselves, for the time being this promise cannot be fulfilled. An unsuccessful attempt to use largely rule-based data mining processes to learn behaviours from game logs led to finding the inherently top-down nature of such processes was fundamentally at odds with the unsupervised bottom-up learning requirement of the problem. Innate issues with game logs toward the goal of unsupervised agent learning are discussed. Possible approaches to the problem subsuming successful applications of various methods in narrower fields are presented for both symbolic and sub-symbolic advocates.