A Lookahead Behavior Model for Multi-Agent Hybrid Simulation
Abstract
:1. Introduction
2. Related Works
2.1. Traditional Agent Behavior Model
2.2. State Update Mechanism in Agent-Based Modeling
2.3. Approaches of Combining DES and Agent-Based Modeling
3. Problem Description
3.1. Context Overview
3.2. Main Problems of the PR
3.2.1. Resynchronization Interval Determination
3.2.2. Cyclic Dependency
- and , is the set of natural numbers,
- is the states of at time ,
- is the external state transition function of .
4. The Lookahead Behavior Model
4.1. Time Window-Based Lookahead
- is the sender of interaction event, and can be or ;
- is the receiver of , and is an alternative choice;
- is the creating time of ;
- is the occurring time of ; and
- represents the corresponding interaction.
Algorithm 1: Time window-based lookahead algorithm. |
Input: next action to be performed at the moment by the primary Agent0: ; duration of action: Variables: // current simulation time Output: 1 2 = getAgentsMayInteractWithAction () 3 for each in the 4 = getCurrentPerformingAction() 5 = predictInteraction(,) 6 for each in the 7 = getPredictedTimeOfInteraction () 8 = getPredictedStateOfInteraction() 9 if() 10 = createEventFrominteraction(, , , ) 11 12 end if 13 end for 14 end for |
4.2. Estimate Value-Based Unlock
5. Case and Experiments
5.1. Case Scenario and Experiment Setup
- (1)
- Fixed time synchronization-based simulation (FS);
- (2)
- Variable time synchronization-based simulation (VS);
- (3)
- Complete resynchronization-based simulation (CR);
- (4)
- Partial resynchronization-based LBM simulation (LBM-PR).
5.2. Modeling of Lookahead
5.3. Experiment Results
6. Discussions
6.1. Characteristics
6.2. Applicable Scope
7. Conclusions and Future Work
Acknowledgments
Author Contributions
Conflicts of Interest
References
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Mechanism | All States Need to Be Updated? | All Agents Need to Be Updated? | Update Synchronizationly or Not? |
---|---|---|---|
FS | Yes | Yes | Synchronizationly |
VS | Yes | Yes | Synchronizationly |
OS | Yes | Yes | Synchronizationly + Asynchronously rollback |
CR | No | Yes | Asynchronously |
PR | No | No | Asynchronously |
Approaches | Degree of Utilizing Efficiency Improvement of DES | Degree of Implementation | Can Dynamics Be Fully Modeled? | Available State Update Mechanism |
---|---|---|---|---|
SD | Completely | Hard | Not | CR/PR |
CTD | Low | Simple | Yes | FS/VS/OS |
PTD | Relatively low | Relatively simple | Yes | FS/VS/OS + CR/PR |
IMD | Completely | Relatively hard | Yes | CR/PR |
Symbol | Nomenclature |
---|---|
The number of agents in the system | |
The th agent, | |
The act performed by the th agent at time and this action is the th action it performs, | |
The time set | |
The current simulation time, | |
The start time of the th action for the th agent , | |
The duration of the th action for the th agent , | |
The state of the th agent at time where | |
The estimated state of the th agent at time predicted at time where | |
The set of all the states of the th agent | |
The set of all the lookahead states of the th agent | |
The sequence of all actions performed by the th agent before time | |
The set of the beginning time of acts performed by the th agent before time | |
The set of all the actions of the th agent | |
The set of the system’s actions | |
The set of the system’s states | |
The internal state transition function of the th agent | |
The external state transition function of the th agent; it indicates that the state transition of the th agent occurred at one specific moment is related to the system’s existing acts and states | |
The lookahead function of the state of the th agent; this implies that the state of the th agent predicted at one specific moment is related to the system’s existing acts and states | |
A compound function of and for the second agent |
Parameter | Value |
---|---|
Size of virtual space | 10,000 × 10,000 |
Number of agents in total | 10, 20, 30, 50, 70, 100, 200, 300, 400, 500, 600 |
Speed of MovingAgent | Random number, 1–100 |
Detection radius of StaticAgent | Random number, 0–50 |
Aspects | Original TBM | Delayed TBM | LBM |
---|---|---|---|
Steps contained in a cycle | Sense, think, and act | Sense, think, and act | Sense, think, lookahead, and act |
The relationship of steps | Serial in a cycle, indispensible for each step | Serial in a cycle with arbitrary delays between two steps, indispensible for think step | Think/sense can be skipped, indispensible for lookahead before each action |
The relationship of cycles | Fixed time interval | Arbitrary delay | Arbitrary |
Ability to conduct simultaneously | No | Yes (except for think step) | Yes |
Number of updates | More | More | Less |
Number of resynchronizations | More | More | Less |
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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. https://doi.org/10.3390/app7101095
Yang M, Peng Y, Ju R-S, Xu X, Yin Q-J, Huang K-D. A Lookahead Behavior Model for Multi-Agent Hybrid Simulation. Applied Sciences. 2017; 7(10):1095. https://doi.org/10.3390/app7101095
Chicago/Turabian StyleYang, Mei, Yong Peng, Ru-Sheng Ju, Xiao Xu, Quan-Jun Yin, and Ke-Di Huang. 2017. "A Lookahead Behavior Model for Multi-Agent Hybrid Simulation" Applied Sciences 7, no. 10: 1095. https://doi.org/10.3390/app7101095
APA StyleYang, M., Peng, Y., Ju, R.-S., Xu, X., Yin, Q.-J., & Huang, K.-D. (2017). A Lookahead Behavior Model for Multi-Agent Hybrid Simulation. Applied Sciences, 7(10), 1095. https://doi.org/10.3390/app7101095