We present a conceptual framework within which we can analyze simple reward schemes for classifier systems. The framework consists of a set of classifiers, a learning mechanism, and a finite automaton environment that outputs payoff. We find that many reward schemes have negative biases that degrade
β¦ LIBER β¦
An approach to active learning for classifier systems
β Scribed by Haifeng Xi; Yupin Luo; Shiyuan Yang
- Publisher
- Springer
- Year
- 1999
- Tongue
- English
- Weight
- 548 KB
- Volume
- 14
- Category
- Article
- ISSN
- 1000-9000
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