Hierarchical multi-agent reinforcement learning
Proceedings of the fifth international conference on Autonomous agents
Formal Specification and Prototyping of Multi-agent Systems
ESAW '00 Proceedings of the First International Workshop on Engineering Societies in the Agent World: Revised Papers
Multi-Agent Reinforcement Leraning for Traffic Light Control
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
Improving reinforcement learning with context detection
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
Biological Network Simulation Using Holonic Multiagent Systems
UKSIM '08 Proceedings of the Tenth International Conference on Computer Modeling and Simulation
A Collaborative Reinforcement Learning Approach to Urban Traffic Control Optimization
WI-IAT '08 Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 02
Opportunities for multiagent systems and multiagent reinforcement learning in traffic control
Autonomous Agents and Multi-Agent Systems
Integrating organizational control into multi-agent learning
Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 2
Holonic Models for Traffic Control Systems
HoloMAS '09 Proceedings of the 4th International Conference on Industrial Applications of Holonic and Multi-Agent Systems: Holonic and Multi-Agent Systems for Manufacturing
Learning in groups of traffic signals
Engineering Applications of Artificial Intelligence
A review of the applications of agent technology in traffic and transportation systems
IEEE Transactions on Intelligent Transportation Systems
A holonic multi-agent model for oil industry supply chain management
IBERAMIA'10 Proceedings of the 12th Ibero-American conference on Advances in artificial intelligence
Formal specification of holonic multi-agent systems framework
ICCS'05 Proceedings of the 5th international conference on Computational Science - Volume Part III
Neural Networks for Real-Time Traffic Signal Control
IEEE Transactions on Intelligent Transportation Systems
Cooperative, hybrid agent architecture for real-time traffic signal control
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Holonification of a network of agents based on graph theory
KES-AMSTA'12 Proceedings of the 6th KES international conference on Agent and Multi-Agent Systems: technologies and applications
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Agent-based technologies are rapidly growing as a powerful tool for modelling and developing large-scale distributed systems. Recently, multi-agent systems are largely used for intelligent transportation systems modelling. Traffic signals control is a challenging issue in this area, especially in a large-scale urban network. In a large traffic network, where each agent represents a traffic signals controller, there are many entities interacting with each other and hence it is a complex system. An approach to reduce the complexity of such systems is using organisation-based multi-agent system. In this paper, we use an organisation called holonic multi-agent system (HMAS) to model a large traffic network. A traffic network containing fifty intersections is partitioned into a number of regions and holons are assigned to control each region. The holons are hierarchically arranged in two levels, intersection controller holons in the first level and region controller holons in the second level. We introduce holonic Q-learning to control the signals in both levels. The inter-level interactions between the holons in the two levels contribute to the learning process. Experimental results show that the holonic Q-learning prevents the network to be over-saturated while it causes less average delay time and higher flow rate.