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This book constitutes the refereed proceedings of the 28th International Conference on Analytical and Stochastic Modelling Techniques and Applications, ASMTA 2024, held in Venice, Italy, on June 14, 2024. The 10 full papers presented were carefully reviewed and selected from 14 submissions. These papers covered a wide range of topics in analytical and stochastic modeling techniques and their applications.
This book constitutes the refereed proceedings of the 28th International Conference on Analytical and Stochastic Modelling Techniques and Applications, ASMTA 2024, held in Venice, Italy, on June 14, 2024.
The 10 full papers presented were carefully reviewed and selected from 14 submissions. These papers covered a wide range of topics in analytical and stochastic modeling techniques and their applications.
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Inhaltsangabe
.- Markov chain aggregation with error bounds on transient distributions. .- Strong Aggregation in the Stochastic matching model with Random Discipline. .- Optimal Allocation of Tasks to Networked Computing Facilities. .- Revenue Management for Parallel Services with Fully Observable Queues. .- Deep reinforcement learning for weakly coupled MDP's with continuous actions. .- A lazy abstraction algorithm for Markov decision processes: theory and initial evaluation. .- Queueing Analysis of an Ensemble Machine Learning System. .- Analysis of load balancing prioritization for heterogeneous M/M/c/K server clusters in the stationary mean-field regime. .- An algebraic proof of the relation of Markov fluid queues and QBD processes. .- Stability of the Multiserver Job Queuing Model with Infinite Resources.
.- Markov chain aggregation with error bounds on transient distributions. .- Strong Aggregation in the Stochastic matching model with Random Discipline. .- Optimal Allocation of Tasks to Networked Computing Facilities. .- Revenue Management for Parallel Services with Fully Observable Queues. .- Deep reinforcement learning for weakly coupled MDP's with continuous actions. .- A lazy abstraction algorithm for Markov decision processes: theory and initial evaluation. .- Queueing Analysis of an Ensemble Machine Learning System. .- Analysis of load balancing prioritization for heterogeneous M/M/c/K server clusters in the stationary mean-field regime. .- An algebraic proof of the relation of Markov fluid queues and QBD processes. .- Stability of the Multiserver Job Queuing Model with Infinite Resources.
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