Syndetics omslagsbild
Bild från Syndetics

Distributed Artificial Intelligence [electronic resource] : Second International Conference, DAI 2020, Nanjing, China, October 24–27, 2020, Proceedings / edited by Matthew E. Taylor, Yang Yu, Edith Elkind, Yang Gao.

Medverkande: Materialtyp: TextSerie: Lecture Notes in Artificial Intelligence ; 12547Utgivningsuppgift: Cham : Springer International Publishing : Imprint: Springer, 2020Utgåva: 1st ed. 2020Beskrivning: 1 online resource (IX, 141 p. 5 illus.)Innehållstyp:
  • text
Medietyp:
  • computer
Bärartyp:
  • online resource
ISBN:
  • 9783030640965
Ämnen: Fler format: Printed edition:: Ingen titel; Printed edition:: Ingen titelDDK-klassifikation:
  • 006.3 23
Library of Congress (LC) klassifikationskod:
  • Q334-342
  • TA347.A78
Onlineresurser:
Innehåll:
Parallel Algorithm for Nash Equilibrium in Multiplayer Stochastic Games with Application to Naval Strategic Planning -- LAC-Nav: Collision-Free Multiagent Navigation Based on The Local ActionCells -- MGHRL: Meta Goal-generation for Hierarchical Reinforcement Learning -- D3PG: Decomposed Deep Deterministic Policy Gradient for Continuous Control -- Lyapunov-Based Reinforcement Learning for Decentralized Multi-Agent Control -- Hybrid Independent Learning in Cooperative Markov Games -- Efficient Exploration By Novelty-Pursuit -- Context-aware Multi-Agent Coordination with Loose Couplings and Repeated Interaction -- Battery Management for Automated Warehouses via Deep Reinforcement Learning.
I: Springer Nature eBookSammanfattning: This book constitutes the refereed proceedings of the Second International Conference on Distributed Artificial Intelligence, DAI 2020, held in Nanjing, China, in October 2020. The 9 full papers presented in this book were carefully reviewed and selected from 22 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. Due to the Corona pandemic this event was held virtually.
Inga fysiska exemplar för denna post

Parallel Algorithm for Nash Equilibrium in Multiplayer Stochastic Games with Application to Naval Strategic Planning -- LAC-Nav: Collision-Free Multiagent Navigation Based on The Local ActionCells -- MGHRL: Meta Goal-generation for Hierarchical Reinforcement Learning -- D3PG: Decomposed Deep Deterministic Policy Gradient for Continuous Control -- Lyapunov-Based Reinforcement Learning for Decentralized Multi-Agent Control -- Hybrid Independent Learning in Cooperative Markov Games -- Efficient Exploration By Novelty-Pursuit -- Context-aware Multi-Agent Coordination with Loose Couplings and Repeated Interaction -- Battery Management for Automated Warehouses via Deep Reinforcement Learning.

This book constitutes the refereed proceedings of the Second International Conference on Distributed Artificial Intelligence, DAI 2020, held in Nanjing, China, in October 2020. The 9 full papers presented in this book were carefully reviewed and selected from 22 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. Due to the Corona pandemic this event was held virtually.

Print version record.

Licensed e-book