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Distributed Artificial Intelligence [electronic resource] : 4th International Conference, DAI 2022, Tianjin, China, December 15–17, 2022, Proceedings /

Contributor(s): Material type: TextTextSeries: Lecture Notes in Artificial Intelligence ; 13824Publisher: Cham : Springer Nature Switzerland : Imprint: Springer, 2023Edition: 1st ed. 2023Description: IX, 103 p. 34 illus., 28 illus. in color. online resourceContent type:
  • text
Media type:
  • computer
Carrier type:
  • online resource
ISBN:
  • 9783031255496
Subject(s): Additional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification:
  • 006.3 23
LOC classification:
  • Q334-342
  • TA347.A78
Online resources:
Contents:
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.
In: Springer Nature eBookSummary: 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. .
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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.

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. .

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