The joint breakthrough of big data, cloud computing and deep learning has made artificial intelligence (AI) the new focus in the international arena. AI is a branch of computer science, developing intelligent machine with imitating, extending and augmenting human intelligence through artificial means and techniques to realize intelligent behaviour.
This comprehensive compendium, consisting of 15 chapters, captures the updated achievements of AI. It is completely revised to reflect the current researches in the field, through numerous techniques and strategies to address the impending challenges facing computer scientists today.
The unique volume is useful for senior or graduate students in the information field and related tertiary specialities. It is also a suitable reference text for professionals, researchers, and academics in AI, machine learning, electrical & electronic engineering and biocomputing.
Contents: - Introduction
- Logic Foundation
- Constraint Reasoning
- Bayesian Network
- Probabilistic Graphic Models
- Case-Based Reasoning
- Inductive Learning
- Statistical Learning
- Deep Learning
- Reinforcement Learning
- Unsupervised Learning
- Association Rules
- Evolutionary Computation
- Multi-Agent Systems
- Internet Intelligence
Readership: Researchers, academics, professionals and senior and graduate students in artificial intelligence, machine learning, electrical and electronic engineering.Constraint Reasoning;Bayesian Network;Probabilistic Graphic Models;Case-Based Reasoning;Inductive Learning;Statistical Learning;Deep Learning;Reinforcement Learning00
