Evolutionary dynamics of multi-agent learning: A survey

D Bloembergen, K Tuyls, D Hennes… - Journal of Artificial …, 2015 - jair.org
The interaction of multiple autonomous agents gives rise to highly dynamic and
nondeterministic environments, contributing to the complexity in applications such as …

Multiagent learning: Basics, challenges, and prospects

K Tuyls, G Weiss - Ai Magazine, 2012 - ojs.aaai.org
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 …

Independent reinforcement learners in cooperative markov games: a survey regarding coordination problems

L Matignon, GJ Laurent, N Le Fort-Piat - The Knowledge …, 2012 - cambridge.org
In the framework of fully cooperative multi-agent systems, independent (non-communicative)
agents that learn by reinforcement must overcome several difficulties to manage to …

A human-centred approach based on functional near-infrared spectroscopy for adaptive decision-making in the air traffic control environment: A case study

Q Li, KKH Ng, Z Fan, X Yuan, H Liu, L Bu - Advanced Engineering …, 2021 - Elsevier
Safety-critical systems like air traffic control (ATC) are usually less automated than might be
expected by the public, so human intelligence will remain at the core in the decision-making …

Social ski driver conditional autoregressive-based deep learning classifier for flight delay prediction

DB Bisandu, I Moulitsas, S Filippone - Neural Computing and Applications, 2022 - Springer
The importance of robust flight delay prediction has recently increased in the air
transportation industry. This industry seeks alternative methods and technologies for more …

[LIBRO][B] Introduction to intelligent systems in traffic and transportation

ALC Bazzan, F Klügl - 2022 - books.google.com
Urban mobility is not only one of the pillars of modern economic systems, but also a key
issue in the quest for equality of opportunity, once it can improve access to other services …

Machine learning approach for flight departure delay prediction and analysis

E Esmaeilzadeh… - Transportation Research …, 2020 - journals.sagepub.com
The expected growth in air travel demand and the positive correlation with the economic
factors highlight the significant contribution of the aviation community to the US economy. On …

Review on artificial intelligence techniques for improving representative air traffic management capability

J Tang, G Liu, Q Pan - Journal of Systems Engineering and …, 2022 - ieeexplore.ieee.org
The use of artificial intelligence (AI) has increased since the middle of the 20th century, as
evidenced by its applications to a wide range of engineering and science problems. Air …

A multi-agent approach for reactionary delay prediction of flights

Y Guleria, Q Cai, S Alam, L Li - IEEE Access, 2019 - ieeexplore.ieee.org
Flight schedules are highly sensitive to delays and witness these events on a very frequent
basis. In an interconnected and interdependent air transportation system, these delays can …

Explaining deep reinforcement learning decisions in complex multiagent settings: towards enabling automation in air traffic flow management

T Kravaris, K Lentzos, G Santipantakis, GA Vouros… - Applied …, 2023 - Springer
With the objective to enhance human performance and maximize engagement during the
performance of tasks, we aim to advance automation for decision making in complex and …