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Authors: Bastian Andelefski and Stefan Schiffer

Affiliation: RWTH Aachen University, Germany

ISBN: 978-989-758-220-2

Keyword(s): Assisted Feature Engineering, Feature Learning, Arcade Learning Environment, Knowledge-Based Agents.

Related Ontology Subjects/Areas/Topics: Agent Models and Architectures ; Agents ; Artificial Intelligence ; Bioinformatics ; Biomedical Engineering ; Biomedical Signal Processing ; Computational Intelligence ; Data Manipulation ; Data Mining ; Databases and Information Systems Integration ; Enterprise Information Systems ; Evolutionary Computing ; Health Engineering and Technology Applications ; Human-Computer Interaction ; Intelligent User Interfaces ; Knowledge Discovery and Information Retrieval ; Knowledge Representation and Reasoning ; Knowledge-Based Systems ; Machine Learning ; Methodologies and Methods ; Neurocomputing ; Neurotechnology, Electronics and Informatics ; Pattern Recognition ; Physiological Computing Systems ; Sensor Networks ; Signal Processing ; Soft Computing ; Symbolic Systems ; Visualization

Abstract: Human knowledge can greatly increase the performance of autonomous agents. Leveraging this knowledge is sometimes neither straightforward nor easy. In this paper, we present an approach for assisted feature engineering and feature learning to build knowledge-based agents for three arcade games within the Arcade Learning Environment. While existing approaches mostly use model-free approaches we aim at creating a descriptive set of features for world modelling and building agents. To this end, we provide (visual) assistance in identifying and modelling features from RAM, we allow for learning features based on labeled game data, and we allow for creating basic agents using the above features. In our evaluation, we compare different methods to learn features from the RAM. We then compare several agents using different sets of manual and learned features with one another and with the state-of-the-art.

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Paper citation in several formats:
Andelefski B. and Schiffer S. (2017). Assisted Feature Engineering and Feature Learning to Build Knowledge-based Agents for Arcade Games.In Proceedings of the 9th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART, ISBN 978-989-758-220-2, pages 228-238. DOI: 10.5220/0006202602280238

@conference{icaart17,
author={Bastian Andelefski and Stefan Schiffer},
title={Assisted Feature Engineering and Feature Learning to Build Knowledge-based Agents for Arcade Games},
booktitle={Proceedings of the 9th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,},
year={2017},
pages={228-238},
publisher={ScitePress},
organization={INSTICC},
doi={10.5220/0006202602280238},
isbn={978-989-758-220-2},
}

TY - CONF

JO - Proceedings of the 9th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART,
TI - Assisted Feature Engineering and Feature Learning to Build Knowledge-based Agents for Arcade Games
SN - 978-989-758-220-2
AU - Andelefski B.
AU - Schiffer S.
PY - 2017
SP - 228
EP - 238
DO - 10.5220/0006202602280238

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