DeepAI AI Chat
Log In Sign Up

Fuzzy Q-Learning Based Multi-Agent System for Intelligent Traffic Control by a Game Theory Approach

04/23/2019
by   Abolghasem Daeichian, et al.
Department of Chemistry Arak University
0

This paper introduces a multi-agent approach to adjust traffic lights based on traffic situation in order to reduce average delay time. In the traffic model, lights of each intersection are controlled by an autonomous agent. Since decision of each agent affects neighbor agents, this approach creates a classical non-stationary environment. Thus, each agent not only needs to learn from the past experience but also has to consider decision of neighbors to overcome dynamic changes of the traffic network. Fuzzy Q-learning and Game theory are employed to make policy based on previous experiences and decision of neighbor agents. Simulation results illustrate the advantage of the proposed method over fixed time, fuzzy, Q-learning and fuzzy Q-learning control methods.

READ FULL TEXT

page 1

page 2

page 3

page 4

07/06/2021

Effects of Smart Traffic Signal Control on Air Quality

Adaptive traffic signal control (ATSC) in urban traffic networks poses a...
10/29/2021

Learning to Communicate with Reinforcement Learning for an Adaptive Traffic Control System

Recent work in multi-agent reinforcement learning has investigated inter...
06/04/2014

A self-organizing system for urban traffic control based on predictive interval microscopic model

This paper introduces a self-organizing traffic signal system for an urb...
12/27/2012

Design of Intelligent Agents Based System for Commodity Market Simulation with JADE

A market of potato commodity for industry scale usage is engaging severa...
12/17/2011

Performance Evaluation of Road Traffic Control Using a Fuzzy Cellular Model

In this paper a method is proposed for performance evaluation of road tr...
03/25/2022

Analysis of OODA Loop based on Adversarial for Complex Game Environments

To address the problem of imperfect confrontation strategy caused by the...
12/07/2012

A simple method for decision making in robocup soccer simulation 3d environment

In this paper new hierarchical hybrid fuzzy-crisp methods for decision m...