Search Results for "multi agent simulation"

This project develops web-based interactive visualisation to support the analysis and monitoring the data from the comprehensive system dynamics and agent based simulation. This work visualise the data via classical charts and graphs in an interactive way. The web-based platform enables upload csv files, mapping and display the attributes based on user’s preference

///////// NOTICE We have migrated to GitHub: https://petavision.github.io To clone an updated repository of the PetaVision codebase, please go to our page on GitHub. ///////// PetaVision is an open source, object oriented neural simulation toolbox optimized for high-performance multi-core, multi-node computer architectures. PetaVision is intended for computational neuroscientists who seek to apply neuromorphic models to hard signal processing problems; both to improve on the performance of existing algorithms and/or to gain insight into the computational mechanisms underlying biological neural processing. ...

This project concerns the design and implementation of an open-source flocking boids simulator, designed as a tool to analyze and characterize flock-like collective emerging behaviors. Each boid is conceived as an active agent and modelled by a point-mass approximation. Boid movements in a 3D space are guided by a set of elementary steering behaviors, each implemented as a force acting on the boid's point mass. Each boid is affected by interactions with both the environment and other boids....

DSOL is a full featured multi-formalism, distributed simulation environment developed at Delft University of Technology (The Netherlands). DSOL has support for discrete event and for continuous modeling. Formalisms supported are event scheduling, DEVS, flow-based simulation, and continuous modeling through sets of differential equations. The first release was introduced at IEEE's Winter Simulation Conference in 2002.

MuLaViTo is a multi-layer visualization framework which allows to visualize relations between multiple graphs in derived applications. Moreover, it provides helpful means like k-shortest path algorithms, running algorithms in a separate thread, ...

KNeTS (Knowledge Elicitation Tools) is a survey tool to create multi-agent models based on local knowledge using pattern analysis to identify rules that are iteratively validated with the informant. The final output is a knowledge-based multi-agent model

distributed simulation agent system developed for prove and populate agent theory in resource planing branch