An Improved Bayesian Learning Method for Multi-agent System
DOI:
https://doi.org/10.3991/ijoe.v11i9.5071Keywords:
Multi-agent system, Intelligent agent, Agent learning, Bayesian learningAbstract
A multi-agent coordinate ion is addressed in urban traffic control, which uses the recursive modeling method (RMM) that enables an agent to select its rational act ion by examining with other agents by modeling their decision making in a distributed multi-agent environment. Bayesian learning is used in conjunction with RMM for belief update. Based on this method, a multi-agent traffic control system is established and the results rated its effective.
Downloads
Published
How to Cite
Issue
Section
License
The submitting author warrants that the submission is original and that she/he is the author of the submission together with the named co-authors; to the extend the submission incorporates text passages, figures, data or other material from the work of others, the submitting author has obtained any necessary permission.
Articles in this journal are published under the Creative Commons Attribution Licence (CC-BY What does this mean?). This is to get more legal certainty about what readers can do with published articles, and thus a wider dissemination and archiving, which in turn makes publishing with this journal more valuable for you, the authors.
By submitting an article the author grants to this journal the non-exclusive right to publish it. The author retains the copyright and the publishing rights for his article without any restrictions.