Evolutionary dynamics of multi-agent learning: A survey
The interaction of multiple autonomous agents gives rise to highly dynamic and
nondeterministic environments, contributing to the complexity in applications such as …
nondeterministic environments, contributing to the complexity in applications such as …
Multi-agent reinforcement learning: An overview
Multi-agent systems can be used to address problems in a variety of domains, including
robotics, distributed control, telecommunications, and economics. The complexity of many …
robotics, distributed control, telecommunications, and economics. The complexity of many …
Mastering the game of Stratego with model-free multiagent reinforcement learning
We introduce DeepNash, an autonomous agent that plays the imperfect information game
Stratego at a human expert level. Stratego is one of the few iconic board games that artificial …
Stratego at a human expert level. Stratego is one of the few iconic board games that artificial …
[图书][B] A concise introduction to decentralized POMDPs
FA Oliehoek, C Amato - 2016 - Springer
This book presents an overview of formal decision making methods for decentralized
cooperative systems. It is aimed at graduate students and researchers in the fields of …
cooperative systems. It is aimed at graduate students and researchers in the fields of …
A comprehensive survey of multiagent reinforcement learning
Multiagent systems are rapidly finding applications in a variety of domains, including
robotics, distributed control, telecommunications, and economics. The complexity of many …
robotics, distributed control, telecommunications, and economics. The complexity of many …
Multiagent learning: Basics, challenges, and prospects
Multiagent systems (MAS) are widely accepted as an important method for solving problems
of a distributed nature. A key to the success of MAS is efficient and effective multiagent …
of a distributed nature. A key to the success of MAS is efficient and effective multiagent …
Multi-agent systems applications in energy optimization problems: A state-of-the-art review
A González-Briones, F De La Prieta, MS Mohamad… - Energies, 2018 - mdpi.com
This article reviews the state-of-the-art developments in Multi-Agent Systems (MASs) and
their application to energy optimization problems. This methodology and related tools have …
their application to energy optimization problems. This methodology and related tools have …
The world of independent learners is not Markovian
GJ Laurent, L Matignon… - International Journal of …, 2011 - content.iospress.com
In multi-agent systems, the presence of learning agents can cause the environment to be
non-Markovian from an agent's perspective thus violating the property that traditional single …
non-Markovian from an agent's perspective thus violating the property that traditional single …
Opportunities for multiagent systems and multiagent reinforcement learning in traffic control
ALC Bazzan - Autonomous Agents and Multi-Agent Systems, 2009 - Springer
The increasing demand for mobility in our society poses various challenges to traffic
engineering, computer science in general, and artificial intelligence and multiagent systems …
engineering, computer science in general, and artificial intelligence and multiagent systems …
Learning in games via reinforcement and regularization
P Mertikopoulos, WH Sandholm - Mathematics of Operations …, 2016 - pubsonline.informs.org
We investigate a class of reinforcement learning dynamics where players adjust their
strategies based on their actions' cumulative payoffs over time—specifically, by playing …
strategies based on their actions' cumulative payoffs over time—specifically, by playing …