Abstract
We discuss the use of Ordinal Conditional Functions (OCF) in the context of Reinforcement Learning while introducing a new revision operator for conditional information. The proposed method is compared to the state-of-the-art method in a small Reinforcement Learning application with added futile information, where generalization proves to be advantageous.
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Häming, K., Peters, G. (2010). An Alternative Approach to the Revision of Ordinal Conditional Functions in the Context of Multi-Valued Logic. In: Diamantaras, K., Duch, W., Iliadis, L.S. (eds) Artificial Neural Networks – ICANN 2010. ICANN 2010. Lecture Notes in Computer Science, vol 6353. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15822-3_25
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DOI: https://doi.org/10.1007/978-3-642-15822-3_25
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