Real-world sequential decision-making tasks are generally complex, requiring trade-offs
between multiple, often conflicting, objectives. Despite this, the majority of research in …

Many challenging tasks such as managing traffic systems, electricity grids, or supply chains
involve complex decision-making processes that must balance multiple conflicting …

Real-world decision-making tasks are generally complicated and require trade-offs between
multiple, even conflicting, objectives. As the advent and great development of advanced …

Multiagent systems (MAS) offer a powerful paradigm for modelling distributed settings that
require robust, scalable, and often decentralised control solutions. Despite its numerous …

Purpose Many practical control problems require achieving multiple objectives, and these
objectives often conflict with each other. The existing multi-objective evolutionary …

Real-world sequential decision-making tasks are usually complex, and require trade-offs
between multiple–often conflicting–objectives. However, the majority of research in …

Navigation apps have become more and more popular, as they give information about the
current traffic state to drivers who then adapt their route choice. In commuting scenarios …

ABSTRACT Multiagent Reinforcement Learning (MARL) has been successfully applied as a
framework for solving distributed traffic optimization problems. Route choice is a challenging …

Transportation forecasting is the area concerned with analyzing, modeling, simulating and
validating mobility models for people in a constructed environment, typically in an urban …

Nowadays, one of the most relevant challenges of a data center is to keep its information
secure. To avoid data leaks and other security problems, data centers have to manage …