Model of Production Planning and Scheduling in Shop Floor Based on Collaboration and Competition

The planning and scheduling in real shop floor is actually achieved by coordination between different persons. In this process, cooperation is mainstream, but competition also exists, for example, the competition between different groups, operators with the same skill, etc. In multi-agent based shop floor management and control system, this competition and cooperation relation must be embodied. The general process of shop floor production planning and scheduling is studied, and a colored Petri-net model for the competition and cooperation process of three main agents in such system to achieve shop floor production planning and scheduling is presented. The evaluating method of bids in bidding process that especially embodies the competition relationship is also presented. This colored Petri-net model gives a clear illustration of this complex coordination process to system designers, effectively promotes the cooperative development.

Study and application of reinforcement learning based on DAI in cooperative strategy of robot soccer

A dynamic cooperation model of multi-agent is established by combining reinforcement learning with distributed artificial intelligence(DAI),in which the concept of individual optimization loses its meaning because of the dependence of repayment on each agent itself and the choice of other agents.Utilizing the idea of DAI,the intellectual unit of each robot and the change of task and environment,each agent can make decisions independently and finish various complicated tasks by communication and reciprocation between each other.The method is superior to other reinforcement learning methods commonly used in the multi-agent system.It can improve the convergence velocity of reinforcement learning,decrease requirements of computer memory,and enhance the capability of computing and logical ratiocinating for agent.The result of a simulated robot soccer match proves that the proposed cooperative strategy is valid.

Hyper-Distributed Hyper-Parallel Self-Organizing Dynamic Scheduling Based on Solitary Wave

This paper presents a new soliton approach to hyper-distributed hyper-parallel self-organizing dynamic scheduling for task allocations among rational autonomous agents in a multi-agent system (MAS). This approach can overcome many drawbacks of other mechanisms currently used for coalition formation and cooperation in MAS. The thorny problems, such as overabundant bid, social behaviors, colony intelligence, variable neighbors, and interdepen-dency, can easily be treated by using the proposed approach, whereas they are very difficult for other conventional approaches. The simulation on a distributed transport scheduling sys-tem shows the soliton approach featured by hyper-parallelism, effectiveness, openness, dynamic alignment and adaption.