Oppositional Concepts in Computational Intelligence
Autor Corporativo: | |
---|---|
Otros Autores: | , |
Formato: | eBook |
Lenguaje: | English |
Publicado: |
Berlin, Heidelberg :
Springer Berlin Heidelberg : Imprint: Springer,
2008.
|
Edición: | 1st ed. 2008. |
Colección: | Studies in Computational Intelligence,
155 |
Materias: | |
Acceso en línea: | https://doi.org/10.1007/978-3-540-70829-2 |
Tabla de Contenidos:
- I: Motivations and Theory
- Opposition-Based Computing
- Antithetic and Negatively Associated Random Variables and Function Maximization
- Opposition and Circularity
- II: Search and Reasoning
- Collaborative vs. Conflicting Learning, Evolution and Argumentation
- Proof-Number Search and Its Variants
- III: Optimization
- Improving the Exploration Ability of Ant-Based Algorithms
- Differential Evolution Via Exploiting Opposite Populations
- Evolving Opposition-Based Pareto Solutions: Multiobjective Optimization Using Competitive Coevolution
- IV: Learning
- Bayesian Ying-Yang Harmony Learning for Local Factor Analysis: A Comparative Investigation
- The Concept of Opposition and Its Use in Q-Learning and Q(?) Techniques
- Two Frameworks for Improving Gradient-Based Learning Algorithms
- V: Real World Applications
- Opposite Actions in Reinforced Image Segmentation
- Opposition Mining in Reservoir Management.