Learning in Cooperative Multi-Agent Systems

Name: Learning in Cooperative Multi-Agent Systems
Brand: Sudwestdeutscher Verlag Fur Hochschulschriften AG
SKU: 9783838110363
Price: 73.1 EUR
Availability: InStock

Distributed Reinforcement Learning Algorithms and their Application to Scheduling Problems

Автор: Thomas Gabel

Език:

Корици: С меки корици

Издател: Sudwestdeutscher Verlag Fur Hochschulschriften AG

Наличност: Външен склад

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In a distributed system, a number of individually acting agents coexist. In order to achieve a commo...

Информация за книгата

Автор

Thomas Gabel

Език

Немски език

Корици

Книга - С меки корици

Издадена

2009

страници

192

EAN

9783838110363

ISBN

3838110366

Enbook ID

06943315

Издател

Sudwestdeutscher Verlag Fur Hochschulschriften AG

Теглоt

263

Размери

152 x 229 x 10

Пълно описание

In a distributed system, a number of individually acting agents coexist. In order to achieve a common goal, coordinated cooperation between the agents is crucial. Many real-world applications are well-suited to be formulated in terms of spatially or functionally distributed entities. Job-shop scheduling represents one such application. Multi-agent reinforcement learning (RL) methods allow for automatically acquiring cooperative policies based solely on a specification of the desired joint behavior of the whole system. However, the decentralization of the control and observation of the system among independent agents has a significant impact on problem complexity. The author Thomas Gabel addresses the intricacy of learning and acting in multi-agent systems by two complementary approaches. He identifies a subclass of general decentralized decision-making problems that features provably reduced complexity. Moreover, he presents various novel model-free multi-agent RL algorithms that are capable of quickly obtaining approximate solutions in the vicinity of the optimum. All algorithms proposed are evaluated in the scope of various established scheduling benchmark problems.

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Learning in Cooperative Multi-Agent Systems

Distributed Reinforcement Learning Algorithms and their Application to Scheduling Problems

Информация за книгата

Пълно описание

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