Titlebook: Simulated Evolution and Learning; 6th International Co Tzai-Der Wang,Xiaodong Li,Xin Yao Conference proceedings 2006 Springer-Verlag Berlin

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Solving Traveling Salesman Problems by Artificial Immune Responsee new model is a quaternion (., ., ., .), where . denotes exterior stimulus or antigen, . denotes the set of valid antibodies, . denotes the set of reaction rules describing the interactions between antibodies, and .denotes the dynamic algorithm describing how the reaction rules are applied to antib

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有毒

Quantum-Inspired Immune Clonal Algorithm for Multiuser Detection in DS-CDMA Systemsles of quantum computing, such as a quantum bit and superposition of states. Like other evolutionary algorithms, QICA is also characterized by the representation of the antibody (individual), the evaluation function, and the population dynamics. However, in QICA, an antibody is proliferated and divi

AXIOM

Innate and Adaptive Principles for an Artificial Immune Systemand peripheral tolerance, and memory cells. An artificial immune system framework is then presented based on the analogies of these natural system components and a rule and feature-based problem representation. A data set for intrusion detection is used to highlight the principles of the framework.

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ABASH

Immune Multi-agent Active Defense Model for Network Intrusion immune agent is introduced. While its logical structure and running mechanism are established. The method which uses antibody concentration to quantitatively describe the degree of intrusion danger is presented. The proposed model implements a multi-layer and distributed active defense mechanism fo

Malcontent

Synthesize

Solving Optimization Problem Using Multi-agent Model Based on Belief Interaction the parameter of learning machine to decide the searching direction and intensity of the Agent in the environment. It is also the interaction information between Agents. Agent has the ability to evaluate its path in the past. In this way, Agent can find optimization object rapidly and avoid partial

collagenase

Continuous Function Optimization Using Hybrid Ant Colony Approach with Orthogonal Design Schemeology integrates the advantages of Ant Colony Optimization (ACO) and Orthogonal Design Scheme (ODS). OSACO is based on the following principles: a) each independent variable space (IVS) of CFO is dispersed into a number of random and movable nodes; b) the carriers of pheromone of ACO are shifted to

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