Next Article in Journal
Contrast-Enhanced Ultrasound Imaging Based on Bubble Region Detection
Next Article in Special Issue
Input–Output Finite Time Stabilization of Time-Varying Impulsive Positive Hybrid Systems under MDADT
Previous Article in Journal
A Stochastic Bi-Level Scheduling Approach for the Participation of EV Aggregators in Competitive Electricity Markets
Previous Article in Special Issue
Heuristic Method for Decision-Making in Common Scheduling Problems
Article Menu
Issue 10 (October) cover image

Export Article

Open AccessArticle
Appl. Sci. 2017, 7(10), 1095;

A Lookahead Behavior Model for Multi-Agent Hybrid Simulation

College of Information System and Management, National University of Defense Technology, Changsha 410073, Hunan, China
Author to whom correspondence should be addressed.
Received: 28 August 2017 / Revised: 17 October 2017 / Accepted: 18 October 2017 / Published: 24 October 2017
(This article belongs to the Special Issue Modeling, Simulation, Operation and Control of Discrete Event Systems)
Full-Text   |   PDF [1973 KB, uploaded 24 October 2017]   |  


In the military field, multi-agent simulation (MAS) plays an important role in studying wars statistically. For a military simulation system, which involves large-scale entities and generates a very large number of interactions during the runtime, the issue of how to improve the running efficiency is of great concern for researchers. Current solutions mainly use hybrid simulation to gain fewer updates and synchronizations, where some important continuous models are maintained implicitly to keep the system dynamics, and partial resynchronization (PR) is chosen as the preferable state update mechanism. However, problems, such as resynchronization interval selection and cyclic dependency, remain unsolved in PR, which easily lead to low update efficiency and infinite looping of the state update process. To address these problems, this paper proposes a lookahead behavior model (LBM) to implement a PR-based hybrid simulation. In LBM, a minimal safe time window is used to predict the interactions between implicit models, upon which the resynchronization interval can be efficiently determined. Moreover, the LBM gives an estimated state value in the lookahead process so as to break the state-dependent cycle. The simulation results show that, compared with traditional mechanisms, LBM requires fewer updates and synchronizations. View Full-Text
Keywords: discrete event simulation; agent-based modeling; time advance mechanism; state update mechanism; time window discrete event simulation; agent-based modeling; time advance mechanism; state update mechanism; time window

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

Share & Cite This Article

MDPI and ACS Style

Yang, M.; Peng, Y.; Ju, R.-S.; Xu, X.; Yin, Q.-J.; Huang, K.-D. A Lookahead Behavior Model for Multi-Agent Hybrid Simulation. Appl. Sci. 2017, 7, 1095.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics



[Return to top]
Appl. Sci. EISSN 2076-3417 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top