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Author: Oliver Kramer

Affiliation: International Computer Science Institute, United States

Keyword(s): Autonomous agents, Symbol grounding, Zero semantical commitment condition, Machine learning, Interface design, Optimization.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Cognitive Systems ; Computational Intelligence ; Evolutionary Computing ; Soft Computing ; Symbolic Systems

Abstract: Autonomous systems gather high-dimensional sensorimotor data with their multimodal sensors. Symbol grounding is about whether these systems can, based on this data, construct symbols that serve as a vehicle for higher symbol-oriented cognitive processes. Machine learning and data mining techniques are geared towards finding structures and input-output relations in this data by providing appropriate interface algorithms that translate raw data into symbols. Can autonomous systems learn how to ground symbols in an unsupervised way, only with a feedback on the level of higher objectives? A target-oriented optimization procedure is suggested as a solution to the symbol grounding problem. It is demonstrated that the machine learning perspective introduced in this paper is consistent with the philosophical perspective of constructivism. Interface optimization offers a generic way to ground symbols in machine learning. The optimization perspective is argued to be consistent with von Glasers feld’s view of the world as a black box. A case study illustrates technical details of the machine symbol grounding approach. (More)

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Paper citation in several formats:
Kramer, O. (2011). MACHINE SYMBOL GROUNDING AND OPTIMIZATION. In Proceedings of the 3rd International Conference on Agents and Artificial Intelligence - Volume 2: ICAART; ISBN 978-989-8425-40-9; ISSN 2184-433X, SciTePress, pages 464-469. DOI: 10.5220/0003274304640469

@conference{icaart11,
author={Oliver Kramer.},
title={MACHINE SYMBOL GROUNDING AND OPTIMIZATION},
booktitle={Proceedings of the 3rd International Conference on Agents and Artificial Intelligence - Volume 2: ICAART},
year={2011},
pages={464-469},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003274304640469},
isbn={978-989-8425-40-9},
issn={2184-433X},
}

TY - CONF

JO - Proceedings of the 3rd International Conference on Agents and Artificial Intelligence - Volume 2: ICAART
TI - MACHINE SYMBOL GROUNDING AND OPTIMIZATION
SN - 978-989-8425-40-9
IS - 2184-433X
AU - Kramer, O.
PY - 2011
SP - 464
EP - 469
DO - 10.5220/0003274304640469
PB - SciTePress

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