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

The Shortest Path (SP) problem resembles a variety of real-world situations where one
needs to find paths between origins and destinations. A generalization of the SP is the …

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

The problem of traffic congestion incurs numerous social and economical repercussions and
has thus become a central issue in every major city in the world. For this work we look at the …

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 …

Multi-objective decision-making and dynamic short-est paths are two areas of research
widely studied and of great importance for computer science, engineering, and economics …

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

In this article, we study the optimal design of High Occupancy Toll (HOT) lanes. The traffic
authority determines the road capacity allocation between HOT lanes and ordinary lanes, as …

This paper introduces a negotiation framework to solve the Multi-Agent Path Finding (MAPF)
Problem for self-interested agents in a decentralized fashion. The framework aims to …

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