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Table of Contents
Intro
Preface
Organization
Abstracts of Keynote and Invited Talks
Tactile Situations: A Basis for Manual Intelligence and Learning
Brain-like Perception and Cognition: Challenges and Thinking
Dealing with Concept Drifts in Data Streams
A Novel Bionic Imaging and Its Intelligent Processing
Skill Learning in Dynamic Scene for Robot Operations
Emerging Artificial Intelligence Technologies in Healthcare
Memory Cognition
Contents
Brain Cognition
Mouse-Brain Topology Improved Evolutionary Neural Network for Efficient Reinforcement Learning
1 Introduction
2 Related Works
3 Methods
3.1 The Allen Mouse Brain Atlas
3.2 The Clustered Hierarchical Circuits
3.3 The Neuron Model
3.4 Coping the Biological Circuits to Artificial Ones
3.5 The Network Learning
4 Experiments
4.1 The Clustered Brain Regions
4.2 The Network Topology from Biological Mouse Brain
4.3 Results with Circuit-46 and Random Networks
4.4 Result Comparison with Different Algorithms
5 Discussion
References
DNM-SNN: Spiking Neural Network Based on Dual Network Model
1 Introduction
2 Methods
2.1 Traditional SNN Supervised Learning Algorithm Framework and Its Limitations
2.2 Proposed Dual-Model Spike Network Supervised Learning Algorithm
2.3 Proposed Multi-channel Mix Module Prediction Method
2.4 The Chosen Network Model
2.5 Selection of Spiking Neurons
3 Experimental Results
3.1 Single- and Dual-Model Resnet11 Performance on the CIFAR-10 Dataset
3.2 Related Work Comparison
4 Conclusion
References
A Memetic Algorithm Based on Adaptive Simulated Annealing for Community Detection
1 Introduction
2 Background
2.1 Modularity
2.2 Normalized Mutual Information
3 Description of MA-ASA
3.1 Segmented Label Propagation
3.2 Selection and Crossover Operation
3.3 Mutation Operation
3.4 Improved Simulated Annealing
3.5 Framework of MA-ASA
4 Experiments and Analysis
4.1 Experimental Settings
4.2 Experimental Results and Analysis
5 Conclusion
References
The Model of an Explanation of Self and Self-awareness Based on Need Evolution
1 Background and Significance
2 The Nature and Needs of Life
2.1 The Nature and Representation of the Self
2.2 The Primary Needs and Principle of Life
3 Evolution and Representation of the Needs of Life
3.1 Needs Representation and Original Self-evolution in Single-Celled and Complex Organisms
3.2 Representation Needs and Self-awareness of Human
4 Self-model Based on the Evolution of Needs
4.1 Iterative Model of Needs Evolution
4.2 Evolutionary Model of the Self
5 Dicussion and Conclusion
References
Spiking Neuron Network Based on VTEAM Memristor and MOSFET-LIF Neuron
1 Introduction
2 Proposed Method
2.1 Leaky Integrate-and-Fire Model
2.2 Design of LIF Circuit
2.3 Correspondence Between Network and Circuit
Preface
Organization
Abstracts of Keynote and Invited Talks
Tactile Situations: A Basis for Manual Intelligence and Learning
Brain-like Perception and Cognition: Challenges and Thinking
Dealing with Concept Drifts in Data Streams
A Novel Bionic Imaging and Its Intelligent Processing
Skill Learning in Dynamic Scene for Robot Operations
Emerging Artificial Intelligence Technologies in Healthcare
Memory Cognition
Contents
Brain Cognition
Mouse-Brain Topology Improved Evolutionary Neural Network for Efficient Reinforcement Learning
1 Introduction
2 Related Works
3 Methods
3.1 The Allen Mouse Brain Atlas
3.2 The Clustered Hierarchical Circuits
3.3 The Neuron Model
3.4 Coping the Biological Circuits to Artificial Ones
3.5 The Network Learning
4 Experiments
4.1 The Clustered Brain Regions
4.2 The Network Topology from Biological Mouse Brain
4.3 Results with Circuit-46 and Random Networks
4.4 Result Comparison with Different Algorithms
5 Discussion
References
DNM-SNN: Spiking Neural Network Based on Dual Network Model
1 Introduction
2 Methods
2.1 Traditional SNN Supervised Learning Algorithm Framework and Its Limitations
2.2 Proposed Dual-Model Spike Network Supervised Learning Algorithm
2.3 Proposed Multi-channel Mix Module Prediction Method
2.4 The Chosen Network Model
2.5 Selection of Spiking Neurons
3 Experimental Results
3.1 Single- and Dual-Model Resnet11 Performance on the CIFAR-10 Dataset
3.2 Related Work Comparison
4 Conclusion
References
A Memetic Algorithm Based on Adaptive Simulated Annealing for Community Detection
1 Introduction
2 Background
2.1 Modularity
2.2 Normalized Mutual Information
3 Description of MA-ASA
3.1 Segmented Label Propagation
3.2 Selection and Crossover Operation
3.3 Mutation Operation
3.4 Improved Simulated Annealing
3.5 Framework of MA-ASA
4 Experiments and Analysis
4.1 Experimental Settings
4.2 Experimental Results and Analysis
5 Conclusion
References
The Model of an Explanation of Self and Self-awareness Based on Need Evolution
1 Background and Significance
2 The Nature and Needs of Life
2.1 The Nature and Representation of the Self
2.2 The Primary Needs and Principle of Life
3 Evolution and Representation of the Needs of Life
3.1 Needs Representation and Original Self-evolution in Single-Celled and Complex Organisms
3.2 Representation Needs and Self-awareness of Human
4 Self-model Based on the Evolution of Needs
4.1 Iterative Model of Needs Evolution
4.2 Evolutionary Model of the Self
5 Dicussion and Conclusion
References
Spiking Neuron Network Based on VTEAM Memristor and MOSFET-LIF Neuron
1 Introduction
2 Proposed Method
2.1 Leaky Integrate-and-Fire Model
2.2 Design of LIF Circuit
2.3 Correspondence Between Network and Circuit