Abstract
The paper presents arguments for why AI methodologies should be informed of both behavioural science and neuroscience studies, and argues why this is possible. Through identifying the resemblance points, we will discuss whether findings of ethology and neuroscience can be used in the process of design and development of non-classical AI systems. To this end, we focus on a specific example that has long been investigated in all the concerned disciplines: the action selection problem. The paper overviews action selection mechanisms in behaviour-based AI and neuroscience in order to identify the commonalities that underly the understanding of action selection in different disciplines, and that may constitute the pieces of a common language with which AI can communicate ideas and findings to and from ethology and neuroscience.
Keywords
- Action Selection
- Behaviour Node
- Subsumption Architecture
- Action Selection Process
- Action Selection Mechanism
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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© 2005 Springer-Verlag Berlin Heidelberg
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Öztürk, P. (2005). Modules, Layers, Hierarchies, and Loops Where Artificial Intelligence Meets Ethology and Neuroscience – In Context of Action Selection. In: Mira, J., Álvarez, J.R. (eds) Mechanisms, Symbols, and Models Underlying Cognition. IWINAC 2005. Lecture Notes in Computer Science, vol 3561. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11499220_2
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DOI: https://doi.org/10.1007/11499220_2
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-26298-5
Online ISBN: 978-3-540-31672-5
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