Mutual Information Gain and Linear/Nonlinear Redundancy for Agent Learning, Sequence Analysis, and Modeling
In many applications, intelligent agents need to identify any structure or apparent randomness in an environment and respond appropriately. We use the relative entropy to separate and quantify the presence of both linear and nonlinear redundancy in a sequence and we introduce the new quantities of t...
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| Format: | Article |
| Language: | English |
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MDPI AG
2020-05-01
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| Series: | Entropy |
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| Online Access: | https://www.mdpi.com/1099-4300/22/6/608 |