... prediction. Commonly used statistical methods contain autoregressive moving average, Winner process, Gaussian process, and so on. Intelligent methods can ... multi-AGV system can execute the transportation task in Introduction 7.
... multi-UAV task assignment and path planning problem. While the two tasks are optimization problems that are commonly ... prediction of the actions of other agents in a decoupled manner. However, learning others' behaviors ...
... predict the final delivery of the product they are tracking, it is not important that they predict the detailed behaviour of each HCD (e.g., the precise trajectory of an AGV). In the next section we describe a general model for a ...
This edited volume is targeted at presenting the latest state-of-the-art methodologies in "Hybrid Evolutionary Algorithms".
... AGV. They applied artificial neural network to realize the learning of preference function and analyzed the adaptive scheduling ... multi-agent reinforcement learning method which scored and learned the selection of paths. Digital twin ...
... predicted that MARL technology will provide more intelligent and efficient solutions for multi-agent systems facing large and complex uncertainty environments, thus further promoting the development of artificial intelligence technology ...
... multi- agent environments . Ghavamzadeh , Mohammad , Ph.D. , University of ... ( AGV ) scheduling problems are used as experimental testbeds to empirically ... task under consideration . In this thesis we study four problems in ...
... tasks that are periodic or aperiodic in nature . Although a ... scheduling information at the organisation level , a group of HCDs may have ... AGV ) . In the next section we describe a general model for a transformation ...
This book presents select peer-reviewed proceedings of the International Conference on Advances in Mechanical Engineering (ICAME 2020).