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Advanced artificial intelligence [[electronic resource] /] / Zhongzhi Shi
Advanced artificial intelligence [[electronic resource] /] / Zhongzhi Shi
Autore Shi Zhongzhi
Pubbl/distr/stampa Hackensack, N.J., : World Scientific, 2011
Descrizione fisica 1 online resource (631 p.)
Disciplina 006.3
Collana Series on intelligence science
Soggetto topico Artificial intelligence
Soggetto genere / forma Electronic books.
ISBN 1-283-23462-9
9786613234629
981-4291-35-8
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Preface; Acknowledgement; Contents; Chapter 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; 1.5.1 Cognitive School; 1.5.2 Logical School; 1.5.3 Behavioral School; 1.6 Automated Reasoning; 1.7 Machine Learning; 1.8 Distributed Artificial Intelligence; 1.9 Artificial Thought Model; 1.10 Knowledge Based Systems; Exercises; Chapter 2 Logic Foundation of Artificial Intelligence; 2.1 Introduction; 2.2 Logic Programming; 2.2.1 Definitions of logic programming
2.11.2 Criteria for a solution to the frame problem2.11.3 Nonmonotonic solving approach of the frame problem; 2.12 Dynamic Description Logic; 2.12.1 Description Logic; 2.12.2 Syntax of dynamic description logic; 2.12.3 Semantics of dynamic description logic; Exercises; Chapter 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 Backjumping3.10 Constraint Relation Processing; 3.10.1 Unit Sharing Strategy for Identical Relation; 3.10.2 Interval Propagation; 3.10.3 Inequality Graph; 3.10.4 Inequality Reasoning; 3.11 Constraint Reasoning System COPS; 3.12 ILOG Solver; Exercise; Chapter 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; 4.5.1 Qualitative state transformation; 4.5.2 QSIM algorithm; 4.6 Algebra Approach; 4.7 Spatial Geometric Qualitative Reasoning
4.7.1 Spatial logic4.7.2 Temporal spatial relation; 4.7.3. Applications of temporal and spatial logic; 4.7.4. Randell algorithm; Exercises; Chapter 5 Case-Based Reasoning; 5.1 Overview; 5.2 Basic Notations; 5.3 Process Model; 5.4 Case Representation; 5.4.1 Semantic Memory Unit; 5.4.2 Memory Network; 5.5 Case Indexing; 5.6 Case Retrieval; 5.7 Similarity Relations in CBR; 5.7.1 Semantic similarity; 5.7.2 Structural similarity; 5.7.3 Goal's features; 5.7.4 Individual similarity; 5.7.5 Similarity assessment; 5.8 Case Reuse; 5.9 Case Retainion; 5.10 Instance-Based Learning
5.10.1 Learning tasks of IBL
Record Nr. UNINA-9910464549703321
Shi Zhongzhi  
Hackensack, N.J., : World Scientific, 2011
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Advanced artificial intelligence [[electronic resource] /] / Zhongzhi Shi
Advanced artificial intelligence [[electronic resource] /] / Zhongzhi Shi
Autore Shi Zhongzhi
Pubbl/distr/stampa Hackensack, N.J., : World Scientific, 2011
Descrizione fisica 1 online resource (631 p.)
Disciplina 006.3
Collana Series on intelligence science
Soggetto topico Artificial intelligence
ISBN 1-283-23462-9
9786613234629
981-4291-35-8
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto Preface; Acknowledgement; Contents; Chapter 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; 1.5.1 Cognitive School; 1.5.2 Logical School; 1.5.3 Behavioral School; 1.6 Automated Reasoning; 1.7 Machine Learning; 1.8 Distributed Artificial Intelligence; 1.9 Artificial Thought Model; 1.10 Knowledge Based Systems; Exercises; Chapter 2 Logic Foundation of Artificial Intelligence; 2.1 Introduction; 2.2 Logic Programming; 2.2.1 Definitions of logic programming
2.11.2 Criteria for a solution to the frame problem2.11.3 Nonmonotonic solving approach of the frame problem; 2.12 Dynamic Description Logic; 2.12.1 Description Logic; 2.12.2 Syntax of dynamic description logic; 2.12.3 Semantics of dynamic description logic; Exercises; Chapter 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 Backjumping3.10 Constraint Relation Processing; 3.10.1 Unit Sharing Strategy for Identical Relation; 3.10.2 Interval Propagation; 3.10.3 Inequality Graph; 3.10.4 Inequality Reasoning; 3.11 Constraint Reasoning System COPS; 3.12 ILOG Solver; Exercise; Chapter 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; 4.5.1 Qualitative state transformation; 4.5.2 QSIM algorithm; 4.6 Algebra Approach; 4.7 Spatial Geometric Qualitative Reasoning
4.7.1 Spatial logic4.7.2 Temporal spatial relation; 4.7.3. Applications of temporal and spatial logic; 4.7.4. Randell algorithm; Exercises; Chapter 5 Case-Based Reasoning; 5.1 Overview; 5.2 Basic Notations; 5.3 Process Model; 5.4 Case Representation; 5.4.1 Semantic Memory Unit; 5.4.2 Memory Network; 5.5 Case Indexing; 5.6 Case Retrieval; 5.7 Similarity Relations in CBR; 5.7.1 Semantic similarity; 5.7.2 Structural similarity; 5.7.3 Goal's features; 5.7.4 Individual similarity; 5.7.5 Similarity assessment; 5.8 Case Reuse; 5.9 Case Retainion; 5.10 Instance-Based Learning
5.10.1 Learning tasks of IBL
Record Nr. UNINA-9910788959703321
Shi Zhongzhi  
Hackensack, N.J., : World Scientific, 2011
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Intelligent Information Processing XII : 13th IFIP TC 12 International Conference, IIP 2024, Shenzhen, China, May 3–6, 2024, Proceedings, Part II / / edited by Zhongzhi Shi, Jim Torresen, Shengxiang Yang
Intelligent Information Processing XII : 13th IFIP TC 12 International Conference, IIP 2024, Shenzhen, China, May 3–6, 2024, Proceedings, Part II / / edited by Zhongzhi Shi, Jim Torresen, Shengxiang Yang
Autore Shi Zhongzhi
Edizione [1st ed. 2024.]
Pubbl/distr/stampa Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024
Descrizione fisica 1 online resource (225 pages)
Disciplina 006.3
Altri autori (Persone) TorresenJim
YangShengxiang
Collana IFIP Advances in Information and Communication Technology
Soggetto topico Artificial intelligence
Artificial Intelligence
ISBN 3-031-57919-4
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto -- Early Anomaly Detection in Hydraulic Pumps Based on LSTM Traffic Prediction Model. -- Dynamic Parameter Estimation for Mixtures of Plackett-Luce Models. -- Recognition of Signal Modulation Pattern Based on Multi-Task Self-Supervised Learning. -- Dependency-Type Weighted Graph Convolutional Network on End-to-End Aspect-Based Sentiment Analysis. -- Utilizing Attention for Continuous Human Action Recognition Based on Multimodal Fusion of Visual and Inertial. -- HARFMR: Human Activity Recognition with Feature Masking and Reconstruction. -- CAPPIMU: A Composite Activities Dataset for Human Activity Recognition Utilizing Plantar Pressure and IMU Sensors. -- Open-Set Sensor Human Activity Recognition Based on Reciprocal Time Series. -- Image Understanding. -- A Concept-Based Local Interpretable Model-agnostic Explanation Approach for Deep Neural Networks in Image Classification. -- A Deep Neural Network-based Segmentation Method for Multimodal Brain Tumor Images. -- Graph Convolutional Networks for Predicting Mechanical Characteristics of 3D Lattice Structures. -- 3D Object Reconstruction with Deep Learning. -- Adaptive Prototype Triplet Loss for Cross-Resolution Face Recognition. -- Hand Gesture Recognition Using a Multi-modal Deep Neural Network.
Record Nr. UNINA-9910847593203321
Shi Zhongzhi  
Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Intelligent Information Processing XII : 13th IFIP TC 12 International Conference, IIP 2024, Shenzhen, China, May 3–6, 2024, Proceedings, Part I / / edited by Zhongzhi Shi, Jim Torresen, Shengxiang Yang
Intelligent Information Processing XII : 13th IFIP TC 12 International Conference, IIP 2024, Shenzhen, China, May 3–6, 2024, Proceedings, Part I / / edited by Zhongzhi Shi, Jim Torresen, Shengxiang Yang
Autore Shi Zhongzhi
Edizione [1st ed. 2024.]
Pubbl/distr/stampa Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024
Descrizione fisica 1 online resource (518 pages)
Disciplina 006.3
Altri autori (Persone) TorresenJim
YangShengxiang
Collana IFIP Advances in Information and Communication Technology
Soggetto topico Artificial intelligence
Artificial Intelligence
ISBN 3-031-57808-2
Formato Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione eng
Nota di contenuto -- Machine Learning. -- Dual Contrastive Learning for Anomaly Detection in Attributed Networks. -- Online Learning in Varying Feature Spaces with Informative Variation. -- Towards A Flexible Accuracy-Oriented Deep Learning Module Inference Latency Prediction Framework for Adaptive Optimization Algorithms. -- Table Orientation Classification Model Based on BERT and TCSMN. -- Divide-and-Conquer Strategy for Large-Scale Dynamic Bayesian Network Structure Learning. -- Entropy-Based Logic Explanations of Differentiable Decision Tree. -- Deep Friendly Embedding Space for Clustering. -- Design and Implementation of Risk Control Model Based on Deep Ensemble Learning Algorithm. -- More Teachers Make Greater Students: Compression of CycleGAN. -- Hybrid integrated dimensionality reduction method based on conformal homeomorphism mapping. -- Natural Language Processing. -- Are Mixture-of-Modality-Experts Transformers Robust to Missing ModalityDuring Training And Inferring?. -- Question Answering Systems Based on Pre-trained Language Models: Recent Progress. -- A BERT-Based Model for Legal Document Proofreading. -- Entity Relation Joint Extraction with Data Augmentation Based on Large Language Model. -- Neural and Evolutionary Computing. -- Empirical Evaluation of Evolutionary Algorithms with Power-Law Ranking Selection. -- An Indicator Based Evolutionary Algorithm for Multiparty Multiobjective Knapsack Problems. -- Ensemble Strategy Based Hyper-Heuristic Evolutionary Algorithm for Many-objective Optimization. -- Rolling Horizon Co-evolution for Snake AI Competition. -- Training Artificial Immune Networks as Standalone Generative Models for Realistic Data Synthesis. -- Structure Optimization for Wide-Channel Plate Heat Exchanger Based on Interval Constraints. -- Genetic algorithm driven by translational mutation operator for the scheduling optimization in the steelmaking-continuous casting production. -- Adaptive Genetic Algorithm with Optimized. -- A Data-driven Framework for Whole-brain Network Modeling with Simultaneous EEG-SEEG Data. -- Recommendation and Social Computing. -- Secure and Negotiate Scheme for Vehicle-to-Vehicle Communications in an IoV. -- Flexible K-anonymity Scheme Suitable for Different Scenarios in Social Networks. -- A Recommendation Algorithm Based on Automatic Meta-Path Generation and Relationship Aggregation. -- Cooperative Coevolution for Cross-City Itinerary Planning. -- Business Intelligence and Risk Control. -- A Stock Price Trend Prediction Method Based on Market Sentiment Factors and Multi-Layer Stacking Ensemble Learning with DualCNN-LSTM Models and Nested -- Heterogeneous Learners. -- Credit Default of P2P Online Loans Based on Logistic. -- FedPV-FS: A Feature Selection Method for Federated Learning in Insurance Precision Marketing. -- FRBBM-Scheme: A Flexible Ratio Virtual Primary Key Generation Approach Based on Binary Matching. -- From Concept to Prototype: Developing and Testing GAAINet for Industrial IoT Intrusion Detection. -- Efficient and Secure Authentication Scheme for Internet of Vehicles. -- Pattern Recognition. -- Research on Wavelet Packet Sample Entropy Features of sEMG Signal in Lower Limb Movement Recognition.
Record Nr. UNINA-9910847582503321
Shi Zhongzhi  
Cham : , : Springer Nature Switzerland : , : Imprint : Springer, , 2024
Materiale a stampa
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui