2021.9.20 Multiagent papers

 

09-14-2021

Exploration in Deep Reinforcement Learning: A Comprehensive Survey
by Tianpei Yang et al

09-16-2021

Reconfigurable Broadcast Networks and Asynchronous Shared-Memory Systems are Equivalent
by A. R. Balasubramanian et al

09-16-2021

Finite Model Property and Bisimulation for LFD
by Raoul Koudijs

09-14-2021

Vision Transformer for Learning Driving Policies in Complex Multi-Agent Environments
by Eshagh Kargar et al

09-16-2021

Comprehensive Multi-Agent Epistemic Planning
by Francesco Fabiano

09-14-2021

Specification and Validation of Autonomous Driving Systems: A Multilevel Semantic Framework
by Marius Bozga et al

09-17-2021

Coordinated Random Access for Industrial IoT With Correlated Traffic By Reinforcement-Learning
by Alberto Rech et al

09-14-2021

Reactive and Safe Road User Simulations using Neural Barrier Certificates
by Yue Meng et al

09-16-2021

DMAPF: A Decentralized and Distributed Solver for Multi-Agent Path Finding Problem with Obstacles
by Poom Pianpak et al

09-17-2021

Security Analysis of Distributed Ledgers and Blockchains through Agent-based Simulation
by Luca Serena et al

09-15-2021

Back to the Future: Efficient, Time-Consistent Solutions in Reach-Avoid Games
by Dennis R. Anthony et al

09-16-2021

Flexible and Explainable Solutions for Multi-Agent Path Finding Problems
by Aysu Bogatarkan

09-16-2021

A Logic-based Multi-agent System for Ethical Monitoring and Evaluation of Dialogues
by Abeer Dyoub et al

09-15-2021

Evolutionary Reinforcement Learning Dynamics with Irreducible Environmental Uncertainty
by Wolfram Barfuss et al

 
Craig Smith