Titlebook: Advances in Swarm Intelligence; 9th International Co Ying Tan,Yuhui Shi,Qirong Tang Conference proceedings 2018 Springer Nature Switzerland

painkillers

Deep-Sarsa Based Multi-UAV Path Planning and Obstacle Avoidance in a Dynamic Environmentined Deep-Sarsa model can guide the UAVs to the target without any collisions. This is the first time that Deep-Sarsa has been developed to achieve autonomous path planning and obstacle avoidance of UAVs in a dynamic environment.

晚来的提名

arrhythmic

Learning Based Target Following Control for Underwater Vehiclesystems. In order to improve the vehicle capacity of self-learning, an SVM based learning approach has been developed. Through genetic algorithm generating and mutating fuzzy rules candidate, SVM learning and optimization, one can obtain optimized fuzzy rules. Tank experiments have been performed to verify the proposed controller.

GOAD

Fuzzy Logic Applied to the Performance Evaluation. Honduran Coffee Sector Caseion-making, creating work algorithms for this policy, which includes multifactorial weights and analysis with measurement indicators that they allow tangible and reliable results. Statistical techniques (ANOVA) are also used to establish relationships between work groups and learn about best practices.

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祖传财产

宣传

Optimal Shape Design of an Autonomous Underwater Vehicle Based on Gene Expression Programming by using multi-objective particle swarm optimization. Finally, results are compared with the hydrodynamic calculations. Result shows the efficiency of the method proposed in the paper in the optimal shape design of an underwater robot.

scotoma

GLANS: GIS Based Large-Scale Autonomous Navigation SystemS database and a robot can move accordingly while being able to detect the obstacles and adjust the path. Moreover, the mapping results can be shared among multi-robots to re-localize a robot in the same area without GPS assistance. It has been proved functioning well in the simulation environment of a campus scenario.

沙发

Ringworm

Young Children and Social Knowledgee related theoretical research results and finally form a set of multiagent research system from the theoretical method to the actual platform verification. Our research system has reference value for multiagent related research.