Distributed Artificial Intelligence

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Details

This book constitutes the refereed proceedings of the 4th International Conference on Distributed Artificial Intelligence, DAI 2022, held in Tianjin, China, in December 2022.

The 5 full papers presented in this book were carefully reviewed and selected from 12 submissions. DAI aims at bringing together international researchers and practitioners in related areas including general AI, multiagent systems, distributed learning, computational game theory, etc., to provide a single, high-profile, internationally renowned forum for research in the theory and practice of distributed AI.


Inhalt
A Distributed RBF-Assisted Differential Evolution for Distributed Expensive Constrained Optimization.- A Flexi Partner Selection Model for the Emergence of Cooperation in N-person Social Dilemmas.- Efficient Deep Reinforcement Learning via Policy-extended Successor Feature Approximator.- Maximal Information Propagation with Limited Resources.- Optimistic Exploration based on Categorical-DQN for Cooperative Markov games.

Weitere Informationen

  • Allgemeine Informationen
    • GTIN 09783031255489
    • Genre Information Technology
    • Auflage 1st edition 2023
    • Editor Makoto Yokoo, Jianye Hao, Yevgeniy Vorobeychik, Hong Qiao
    • Lesemotiv Verstehen
    • Anzahl Seiten 116
    • Größe H235mm x B155mm x T7mm
    • Jahr 2023
    • EAN 9783031255489
    • Format Kartonierter Einband
    • ISBN 3031255488
    • Veröffentlichung 22.03.2023
    • Titel Distributed Artificial Intelligence
    • Untertitel 4th International Conference, DAI 2022, Tianjin, China, December 15-17, 2022, Proceedings
    • Gewicht 189g
    • Herausgeber Springer Nature Switzerland
    • Sprache Englisch

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