Distributed Artificial Intelligence: Second International Conference, DAI 2020, Nanjing, China, October 24-27, 2020, Proceedings

by Matthew E. Taylor (Editor), Yang Yu (Editor), Edith Elkind (Editor), Yang Gao (Editor)

Overview

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.

Product Details

ISBN-13:	9783030640965
Publisher:	Springer-Verlag New York, LLC
Publication date:	11/25/2020
Series:	Lecture Notes in Computer Science , #12547
Sold by:	Barnes & Noble
Format:	eBook
File size:	18 MB
Note:	This product may take a few minutes to download.

Table of Contents

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.