Stefan Bosse: Self-adaptive Traffic and Logistics Flow Control using Learning Agents and Ubiquitous Sensors

Self-adaptive Traffic and Logistics Flow Control using Learning Agents and Ubiquitous Sensors

Stefan Bosse

University of Bremen, Dept. Mathematics & Computer Science, Bremen, Germany

sbosse@uni-bremen.de

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Stefan Bosse: Self-adaptive Traffic and Logistics Flow Control using Learning Agents and Ubiquitous Sensors

Introduction

Motivation and Objectives

This work demonstrates the benefits of agent-based simulation and learning agents for the self-organised and decentralised optimisation of traffic and logistics flows in cities

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Stefan Bosse: Self-adaptive Traffic and Logistics Flow Control using Learning Agents and Ubiquitous Sensors

Methods and Paradigms

This work addresses three paradigms to create smart city control:

  1. Cooperating and interacting Multi-agent Systems;

  2. Reinforcement Learning (RL);

    • Rule-based control + Unsupervised Learning
  3. Self-organisation and self-adaptivity.