Distributed AI in the Modern World : Technical and Social Aspects of Interacting Intelligent Agents (Advances in Biomedical Informatics)

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Distributed AI in the Modern World : Technical and Social Aspects of Interacting Intelligent Agents (Advances in Biomedical Informatics)

Olaru, Andrei (EDT)/ Nardin, Luis Gustavo (EDT)/ Sorici, Alexandru (EDT)

ウェブストア価格 ¥39,789（本体¥36,172）
Morgan Kaufmann Publishers In（2026/05発売）
外貨定価 US$ 180.00
ポイント 361pt

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製本 Paperback:紙装版/ペーパーバック版／ページ数 250 p.
言語 ENG
商品コード 9780443446795

Full Description

Distributed AI in the Modern World: Technical and Social Aspects of Interacting Intelligent Agents presents state-of-the-art insights into the various forms of distribution of artificial intelligence, with practical application instances. Sections provide readers with practical solutions at an architectural level, with solutions presented on the distribution of the learning process and the utilization of machine learning models in a distributed system, tools that enable the distribution and interaction of artificial learning entities, how multi-agent systems and machine learning can be combined, the physical embodiment of intelligent agents, and the interaction of intelligent computing units bound to physical space.

Following sections emphasize the challenges that are common to all scenarios and solutions that apply in a wider range of cases. This book does not analyze the internal workings of machine learning models (for instance, in the case of multi-agent reinforcement learning), but instead provides readers with an overview of the challenges brought by the need of artificially intelligent entities to interact with other entities and with their environments, along with practical solutions at an architectural level.

Part 1. Models and applications of distributed machine learning
1. Federated learning solutions and applications
2. Distributed multi-agent learning
3. Models for machine learning on the edge of the network
4. Sharing knowledge about machine learning models in a community of agents

Part 2. Infrastructures for distributed AI
5. Integration of machine learning models in agent-based applications
6. Frameworks for organizing heterogeneous entities and resources in complex scenarios
7. Adaptive interaction across heterogeneous electronic environments

Part 3. Agents in the real-world
8. Interaction in swarms of physically deployed robots
9. Interaction in social humanoid robots
10. Socio-technical networks and hyperagents
11. Web of things and autonomous agents