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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.
(source: Nielsen Book Data)

• Machine generated contents note: ch. 1 Introduction
• 1.1. Brief History of AI
• 1.2. Cognitive Issues of AI
• 1.3. Hierarchical Model of Thought
• 1.4. Symbolic Intelligence
• 1.5. Research Approaches of Artificial Intelligence
• 1.6. Automated Reasoning
• 1.7. Machine Learning
• 1.8. Distributed Artificial Intelligence
• 1.9. Artificial Thought Model
• 1.10. Knowledge Based Systems
• Exercises
• ch. 2 Logic Foundation of Artificial Intelligence
• 2.1. Introduction
• 2.2. Logic Programming
• 2.3. Nonmonotonic Logic
• 2.4. Closed World Assumption
• 2.5. Default Logic
• 2.6. Circumscription Logic
• 2.7. Nonmonotonic Logic NML
• 2.8. Autoepistemic Logic
• 2.9. Truth Maintenance System
• 2.10. Situation Calculus
• 2.11. Frame Problem
• 2.12. Dynamic Description Logic
• Exercises
• ch. 3 Constraint Reasoning
• 3.1. Introduction
• 3.2. Backtracking
• 3.3. Constraint Propagation
• 3.4. Constraint Propagation in Tree Search
• 3.5. Intelligent Backtracking and Truth Maintenance.

• 3.6. Variable Instantiation Ordering and Assignment Ordering
• 3.7. Local Revision Search
• 3.8. Graph-based Backjumping
• 3.9. Influence-based Backjumping
• 3.10. Constraint Relation Processing
• 3.11. Constraint Reasoning System COPS
• 3.12. ILOG Solver
• Exercise
• ch. 4 Qualitative Reasoning
• 4.1. Introduction
• 4.2. Basic approaches in qualitative reasoning
• 4.3. Qualitative Model
• 4.4. Qualitative Process
• 4.5. Qualitative Simulation Reasoning
• 4.6. Algebra Approach
• 4.7. Spatial Geometric Qualitative Reasoning
• Exercises
• ch. 5 Case-Based Reasoning
• 5.1. Overview
• 5.2. Basic Notations
• 5.3. Process Model
• 5.4. Case Representation
• 5.5. Case Indexing
• 5.6. Case Retrieval
• 5.7. Similarity Relations in CBR
• 5.8. Case Reuse
• 5.9. Case Retainion
• 5.10. Instance-Based Learning
• 5.11. Forecast System for Central Fishing Ground
• Exercises
• ch. 6 Probabilistic Reasoning
• 6.1. Introduction
• 6.2. Foundation of Bayesian Probability
• 6.3. Bayesian Problem Solving
• 6.4. Naive Bayesian Learning Model.

• 6.5. Construction of Bayesian Network
• 6.6. Bayesian Latent Semantic Model
• 6.7. Semi-supervised Text Mining Algorithms
• Exercises
• ch. 7 Inductive Learning
• 7.1. Introduction
• 7.2. Logic Foundation of Inductive Learning
• 7.3. Inductive Bias
• 7.4. Version Space
• 7.5. AQ Algorithm for Inductive Learning
• 7.6. Constructing Decision Trees
• 7.7. ID3 Learning Algorithm
• 7.8. Bias Shift Based Decision Tree Algorithm
• 7.9. Computational Theories of Inductive Learning
• Exercises
• ch. 8 Support Vector Machine
• 8.1. Statistical Learning Problem
• 8.2. Consistency of Learning Processes
• 8.3. Structural Risk Minimization Inductive Principle
• 8.4. Support Vector Machine
• 8.5. Kernel Function
• Exercises
• ch. 9 Explanation-Based Learning
• 9.1. Introduction
• 9.2. Model for EBL
• 9.3. Explanation-Based Generalization
• 9.4. Explanation Generalization using Global Substitutions
• 9.5. Explanation-Based Specialization
• 9.6. Logic Program of Explanation-Based Generalization
• 9.7. SOAR Based on Memory Chunks.

• 9.8. Operationalization
• 9.9. EBL with imperfect domain theory
• Exercises
• ch. 10 Reinforcement Learning
• 10.1. Introduction
• 10.2. Reinforcement Learning Model
• 10.3. Dynamic Programming
• 10.4. Monte Carlo Methods
• 10.5. Temporal-Difference Learning
• 10.6. Q-Learning
• 10.7. Function Approximation
• 10.8. Reinforcement Learning Applications
• Exercises
• ch. 11 Rough Set
• 11.1. Introduction
• 11.2. Reduction of Knowledge
• 11.3. Decision Logic
• 11.4. Reduction of Decision Tables
• 11.5. Extended Model of Rough Sets
• 11.6. Experimental Systems of Rough Sets
• 11.7. Granular Computing
• 11.8. Future Trends of Rough Set Theory
• Exercises
• ch. 12 Association Rules
• 12.1. Introduction
• 12.2. The Apriori Algorithm
• 12.3. FP-Growth Algorithm
• 12.4. CFP-Tree Algorithm
• 12.5. Mining General Fuzzy Association Rules
• 12.6. Distributed Mining Algorithm For Association Rules
• 12.7. Parallel Mining of Association Rules
• Exercises
• ch. 13 Evolutionary Computation
• 13.1. Introduction
• 13.2. Formal Model of Evolution System Theory.

• 13.3. Darwin's Evolutionary Algorithm
• 13.4. Classifier System
• 13.5. Bucket Brigade Algorithm
• 13.6. Genetic Algorithm
• 13.7. Parallel Genetic Algorithm
• 13.8. Classifier System Boole
• 13.9. Rule Discovery System
• 13.10. Evolutionary Strategy
• 13.11. Evolutionary Programming
• Exercises
• ch. 14 Distributed Intelligence
• 14.1. Introduction
• 14.2. The Essence of Agent
• 14.3. Agent Architecture
• 14.4. Agent Communication Language ACL
• 14.5. Coordination and Cooperation
• 14.6. Mobile Agent
• 14.7. Multi-Agent Environment MAGE
• 14.8. Agent Grid Intelligence Platform
• Exercises
• ch. 15 Artificial Life
• 15.1. Introduction
• 15.2. Exploration of Artificial Life
• 15.3. Artificial Life Model
• 15.4. Research Approach of Artificial Life
• 15.5. Cellular Automata
• 15.6. Morphogenesis Theory
• 15.7. Chaos Theories
• 15.8. Experimental Systems of Artificial Life
• Exercises.

Artificial intelligence is a branch of computer science and a discipline in the study of machine intelligence, that is, developing intelligent machines or intelligent systems imitating, extending and augmenting human intelligence through artificial means and techniques to realize intelligent behavior.Advanced Artificial Intelligence consists of 16 chapters. The content of the book is novel, reflects the research updates in this field, and especially summarizes the author's scientific efforts over many years. The book discusses the methods and key technology from theory, algorithm, system and applications related to artificial intelligence. This book can be regarded as a textbook for senior students or graduate students in the information field and related tertiary specialities. It is also suitable as a reference book for relevant scientific and technical personnel.
(source: Nielsen Book Data)

• The AI Journey: The Road Traveled and the (Long) Road Ahead / Ramon Lopez de Mantaras
• Transfer Learning and Applications / Qiang Yang
• Semantics of Cyber-Physical Systems / Tharam Dillon, Elizabeth Chang, Jaipal Singh and Omar Hussain
• Big Data Mining in the Cloud / Zhongzhi Shi
• Research on Semantic Programming Language / Shi Ying
• Effectively Constructing Reliable Data for Cross-Domain Text Classification / Fuzhen Zhuang, Qing He and Zhongzhi Shi
• Improving Transfer Learning by Introspective Reasoner / Zhongzhi Shi, Bo Zhang and Fuzhen Zhuang
• PPLSA: Parallel Probabilistic Latent Semantic Analysis Based on MapReduce / Ning Li, Fuzhen Zhuang, Qing He and Zhongzhi Shi
• Analysis on Limitation Origins of Information Theory / Yong Wang, Huadeng Wang and Qiong Cao
• Intelligent Inventory Control: Is Bootstrapping Worth Implementing? / Tatpong Katanyukul, Edwin K.P. Chong and William S. Duff
• Support Vector Machine with Mixture of Kernels for Image Classification / Dongping Tian, Xiaofei Zhao and Zhongzhi Shi.

• The BDIP Software Architecture and Running Mechanism for Self-Organizing MAS / Yi Guo, Xinjun Mao, Fu Hou, Cuiyun Hu and Jianming Zhao
• Optimization of Initial Centroids for K-Means Algorithm Based on Small World Network / Shimo Shen and Zuqiang Meng
• ECCO: A New Evolutionary Classifier with Cost Optimisation / Adam Omielan and Sunil Vadera
• Reasoning Theory for D3L with Compositional Bridge Rules / Xiaofei Zhao, Dongping Tian, Limin Chen and Zhongzhi Shi
• Semantic Keyword Expansion: A Logical Approach / Limin Chen
• An ABox Abduction Algorithm for the Description Logic ALCI / Yanwei Ma, Tianlong Gu, Binbin Xu and Liang Chang
• Reasoning about Assembly Sequences Based on Description Logic and Rule / Yu Meng, Tianlong Gu and Liang Chang
• Dynamic Logic for the Semantic Web / Liang Chang, Qicheng Zhang, Tianlong Gu and Zhongzhi Shi
• On the Support of Ad-Hoc Semantic Web Data Sharing / Jing Zhou, Kun Yang, Lei Shi and Zhongzhi Shi
• An Architecture Description Language Based on Dynamic Description Logics / Zhuxiao Wang, Hui Peng, Jing Guo, Ying Zhang and Kehe Wu, et al.

• Query Expansion Based-on Similarity of Terms for Improving Arabic Information Retrieval / Khaled Shaalan, Sinan Al-Sheikh and Farhad Oroumchian
• Towards an Author Intention Based Computational Model of Story Generation / Feng Zhu and Cungen Cao
• Adaptive Algorithm for Interactive Question-Based Search / Jacek Rzeniewicz, Julian Szymański and Włodzisław Duch
• Research of Media Material Retrieval Scheme Based on XPath / Shuang Feng and Weina Zhang
• Construction of SCI Publications Information System for Statistic / Xie Wu, Huimin Zhang and Jingbo Jiang
• Symbolic ZBDD Representations for Mechanical Assembly Sequences / Fengying Li, Tianlong Gu, Guoyong Cai and Liang Chang
• The Representation of Indiscernibility Relation Using ZBDDs / Qianjin Wei, Tianlong Gu, Fengying Li and Guoyong Cai
• Symbolic OBDD Assembly Sequence Planning Algorithm Based on Unordered Partition with 2 Parts of a Positive Integer / Zhoubo Xu, Tianlong Gu and Rongsheng Dong
• A Representation Model of Geometrical Tolerances Based on First Order Logic / Yuchu Qin, Yanru Zhong, Liang Chang and Meifa Huang.

• Modeling Group Emotion Based on Emotional Contagion / Yanjun Yin, Weiqing Tang and Weiqing Li
• Hierarchical Overlapping Community Discovery Algorithm Based on Node Purity / Guoyong Cai, Ruili Wang and Guobin Liu
• Finding Topic-Related Tweets Using Conversational Thread / Peng Cao, Shenghua Liu, Jinhua Gao, Huawei Shen and Jingyuan Li, et al.
• Messages Ranking in Social Network / Bo Li, Fengxian Shi and Enhong Chen
• Diagnosis of Internetware Systems Using Dynamic Description Logic / Kun Yang, Weiqun Cui, Junheng Teng and Chenzhe Hang
• Reasoning about Semantic Web Services with an Approach Based on Temporal Description Logic / Juan Wang, Liang Chang, Chuangying Zhu and Rongsheng Dong
• Constraint Programming-Based Virtual Machines Placement Algorithm in Datacenter / Yonghong Yu and Yang Gao
• Recommendation-Based Trust Model in P2P Network Environment / Yueju Lei and Guangxi Chen
• Frequency-Adaptive Cluster Head Election in Wireless Sensor Network / Tianlong Yun, Wenjia Niu, Xinghua Yang, Hui Tang and Song Ci.

• A Cluster-Based Multilevel Security Model for Wireless Sensor Networks / Chao Lee, Lihua Yin and Yunchuan Guo
• A New Security Routing Algorithm Based on MST for Wireless Sensor Network / Meimei Zeng and Hua Jiang
• A Novel Model for Semantic Learning and Retrieval of Images / Zhixin Li, ZhiPing Shi, ZhengJun Tang and Weizhong Zhao
• Automatic Image Annotation and Retrieval Using Hybrid Approach / Zhixin Li, Weizhong Zhao, Zhiqing Li and Zhiping Shi
• Double Least Squares Pursuit for Sparse Decomposition / Wanyi Li, Peng Wang and Hong Qiao
• Ensemble of k-Labelset Classifiers for Multi-label Image Classification / Dapeng Zhang and Xi Liu
• Robust Palmprint Recognition Based on Directional Representations / Hengjian Li, Lianhai Wang and Zutao Zhang
• FPGA-Based Image Acquisition System Designed for Wireless / Haohao Yuan, Jianhe Zhou and Suqiao Li
• A Context-Aware Multi-Agent Systems Architecture for Adaptation of Autonomic Systems / Kaiyu Wan and Vasu Alagar
• Eyes Closeness Detection Using Appearance Based Methods / Xue Liu, Xiaoyang Tan and Songcan Chen.

This book constitutes the refereed proceedings of the 7th IFIP TC 12 International Conference on Intelligent Information Processing, IIP 2012, held in Guilin, China, in October 2012. The 39 revised papers presented together with 5 short papers were carefully reviewed and selected from more than 70 submissions. They are organized in topical sections on machine learning, data mining, automatic reasoning, semantic web, information retrieval, knowledge representation, social networks, trust software, internet of things, image processing, and pattern recognition.