A simulation environment for scheduling workflows in multi-agent systems

Author(s):  
Fu-Shiung Hsieh ◽  
Jim-Bon Lin
2005 ◽  
Vol 4 (2) ◽  
pp. 83-94 ◽  
Author(s):  
Hala Mostafa ◽  
Reem Bahgat

As scientists from various domains increasingly resort to agent-based simulation for a more thorough understanding of real-world phenomena, the need for a simulation environment that facilitates rapid development of multi-agent systems is growing. Such a platform should provide means of visualizing the simulated scenario. In this paper we present the agent visualization system, the first system of its kind to specifically focus on catering to the visualization needs of agent-based simulation. The proposed system is a generic add-on that equips a simulation environment with a rich set of visualization facilities offering a variety of textual and graphical browsers that allow the modeler to detect trends and relationships in the simulation scenario. Some techniques from the field of information visualization were adapted and added to the system, while others were devised especially to be used in it. Regardless of their origin, all visualization techniques were thoroughly revised to make them generic enough to fit in our generic system. Agent visualization is more challenging than traditional information visualization in more than one respect. One of them is that the data to be visualized is not static; the simulation system is constantly producing data with every time step. Moreover, the sheer amount of data, together with its diversity, call for special adaptations to ensure that the system remains responsive and generic. To illustrate the various features of the proposed agent visualization system, we present a visualization of MicroTerra; a simulation scenario involving a group of beings trying to maximize their food intake.


2020 ◽  
Vol 08 (03) ◽  
pp. 253-260
Author(s):  
Jason Gibson ◽  
Tristan Schuler ◽  
Loy McGuire ◽  
Daniel M. Lofaro ◽  
Donald Sofge

This work develops and implements a multi-agent time-based path-planning method using A*. The purpose of this work is to create methods in which multi-agent systems can coordinate actions and complete them at the same time. We utilized A* with constraints defined by a dynamic model of each agent. The model for each agent is updated during each time step and the resulting control is determined. This results in a translational path that each of the agents is physically capable of completing in synchrony. The resulting path is given to the agents as a sequence of waypoints. Periodic updates of the path are calculated, utilizing real-world position and velocity information, as the agents complete the task to account for external disturbances. Our methodology is tested in a dynamic simulation environment as well as on real-world lighter-than-air robotic agents.


Author(s):  
Goran Trajkovski

In this chapter we overview our simulation environment (Multi-Agent Systems Simulations [MASim]) that we developed, with the intention of studying behaviors in smaller societies of agents. We will give a gallery of selected recorded behaviors and brief comments on each.


2018 ◽  
Vol 25 (1) ◽  
Author(s):  
Alexandre de O. Zamberlan ◽  
Guilherme C. Kurtz ◽  
Tomas L. Gomes ◽  
Rafael H. Bordini ◽  
Solange B. Fagan

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