Multi agent reinforcement learning цена в августе 2026, обзор, описание, фото, характеристики. Купить Multi agent reinforcement learning с доставкой на дом.

Multi-Agent Reinforcement Learning

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Amit Konar Multi-Agent Coordination

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Discover the latest developments in multi-robot coordination techniques with this insightful and original resource Multi-Agent Coordination: A Reinforcement Learning Approach delivers a comprehensive, insightful, and unique treatment of the development of multi-robot coordination algorithms with
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H. M. Schwartz Multi-Agent Machine Learning

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The book begins with a chapter on traditional methods of supervised learning, covering recursive least squares learning, mean square error methods, and stochastic approximation. Chapter 2 covers single agent reinforcement learning. Topics include learning value functions, Markov games, and TD
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Shiping Yang Iterative Learning Control for Multi-agent Systems Coordination

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A timely guide using iterative learning control (ILC) as a solution for multi-agent systems (MAS) challenges, showcasing recent advances and industrially relevant applications Explores the synergy between the important topics of iterative learning control (ILC) and multi-agent systems (MAS)
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Giovanni Caire Developing Multi-Agent Systems with JADE

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Learn how to employ JADE to build multi-agent systems! JADE (Java Agent DEvelopment framework) is a middleware for the development of applications, both in the mobile and fixed environment, based on the Peer-to-Peer intelligent autonomous agent approach. JADE enables developers to implement and
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Michael Wooldridge Programming Multi-Agent Systems in AgentSpeak using Jason

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Jason is an Open Source interpreter for an extended version of AgentSpeak – a logic-based agent-oriented programming language – written in Java™. It enables users to build complex multi-agent systems that are capable of operating in environments previously considered too unpredictable for computers
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Parag Kulkarni Reinforcement and Systemic Machine Learning for Decision Making

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Reinforcement and Systemic Machine Learning for Decision Making There are always difficulties in making machines that learn from experience. Complete information is not always available—or it becomes available in bits and pieces over a period of time. With respect to systemic learning, there is a
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