NetLogo vs. Repast Simphony? [closed]
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Improve this questionI would like to simulate some scenarios using the multiagent paradigm, and it seems NetLogo and Repast are the most popular tools for that.
I'd like to know if anyone has had any experience with either one and could tell me more about them? For example, I've noticed that there is a fluxogram-like modeling option for Repast, but I believe it is rather limited. I've looked around the tutorials and documentation in the official site, and the documentation seems to be lacking. While there are some examples with it, I'd say extending it to simulate an ambient which it has not been specifically prepared to seems like an unreachable goal at the moment, despite Repast obviously being very robust and apparently able to handle it, given enough familiarity with it.
On the other hand, NetLogo has more examples and overall I've liked it more for its simplicity, but it seems to be more focused on the simulating propagation of diseases or similar models. I've found a programming book teaching Logo, so I figure it'd be easier to get started with it too.
Currently, I am thinking of simulating botnets and IDSes as multiagents. The problem, however, is that I would have to abstract the network and transport layers to an extent to be able to do it, as well as generate traffic between the nodes. Repast is apparently more fitting for this, but given its complexity and lack of documentation I'm thinking of using NetLogo. While there are some examples of NetLogo with traditional applications (ex: Tetris or Pac-Man), I'm not sure about how appropriate it'd be for that.
I have a webpage with a couple dozed netlogo multiagent simulations. I use netlogo for teaching and I have found that, once you get past the learning curve, you can develop simulations amazingly fast. Stuff that would take you 80 man-hours in other so-called agent environments (Jade, Repast, which are really mostly just programming libraries) can be done in 2 hours.
On the other hand, netlogo is not really good for simulations that require immense amount of details, like say simulating a network all the way from TCP/IP to HTTP. That would just require large amounts of code, regardless of programming language, and netlogo currently sucks if your program ends up being more that 10 pages long. Having said that, most people would be amazed at what you can get done in 10 pages of netlogo code.
Short answer: it depends on the programming paradigm or language you want to use, and the design you want for your agents:
If you want a low-entry-high-ceiling language allowing quick prototyping but sophisticated simulations, and are willing to learn a new paradigm (avoiding loops) use NetLogo. Good documentation.
If you want to make a real application to use on highly-parallelized clusters or just want to use Java Groovy or need a specific Java library for your purpose, use Repast or better Repast for High Performance Computing (but avoid ReLogo which is very slow). Mild documentation.
If you want to model cognitive agents (instead of reactive) with FIPA communications, better use Jason or better JaCaMo which supports AgentSpeak + Java (so you can also use your favourite Java libraries), and there's no Groovy required. Bad documentation (a lot of non detailed features and commands and bad too-complex-not-commented examples).
Long answer: Disclaimer: I am more experienced with NetLogo but I also used Repast and a few others like Jason.
Basically, the difference between NetLogo and Repast is that with NetLogo you will have a simpler framework but you'll need to learn how to program in a turtle-and-patch-oriented paradigm, while in Repast you will have to learn that + the mechanisms behind Java Groovy but you will eventually get more flexibility. Speed isn't really a criteria here (see below).
To be more clear, you can program efficiently in NetLogo if you use to a maximum the turtles and the patchs native functions. For example, if you want to implement A*, instead of implementing a list of nodes, you should directly use the patchs and filter them using stuffs like this:
ask patchs with [criteria1 = value and criteria2 = value2] [do-some-stuff]
ask patchs with-min [criteria][do]
let var [somevalue] of min-one-of patches [criteria]
Also if you can't find a way to efficiently do what you want, be sure to check if maybe an extension exists (check also here under Libraries and Tools) for your purpose, like the now native matrix extension which allowed me to make an efficient neural network in NetLogo.
On the other hand, Repast is potentially more flexible than NetLogo (since you have access to the whole range of Java libraries), but a bit more complex since you have to know how to handle Groovy.
If you are solely interested in speed, do NOT use ReLogo (NetLogo-like syntax for Repast) which has been shown to be a whole lot slower than NetLogo (see the 2012 paper below). In any cases, your best bet would either to try an implementation with NetLogo using the tricks above, or if you want to use your application for real later, there is also a distribution called Repast for High Performance Computing which removes most of the overload that come with turtles and patchs objects, and thus it can be used for real applications. A similar extension exists for NetLogo to compute in clusters with parallelization but it's not an official distribution.
If you want more infos about the diverse platforms, here is a nice review of 2006:
Railsback, S. F., Lytinen, S. L., & Jackson, S. K. (2006). Agent-based Simulation Platforms: Review and Development Recommendations. SIMULATION, 82(9), 609-623.
And an updated version of this paper in 2012 dealing with NetLogo vs ReLogo:
Lytinen, S. L., & Railsback, S. F. (2012, April). The evolution of agent-based simulation platforms: A review of netlogo 5.0 and relogo. In Proceedings of the Fourth International Symposium on Agent-Based Modeling and Simulation.
/EDIT: I cited Jason but didn't give any more details. If you want to model cognitive agents (instead of reactive agents), you can do that in NetLogo using the unofficial BDI extension which works well but is a bit limited (but it's easily extensible since it's pure NetLogo), but your best bet is to use a framework specifically designed to model cognitive agent with full support of AgentSpeak.
Jason is very nice since you have access to a full AgentSpeak language + JAVA to implement the technical side. In fact, you can do whole projects using only AgentSpeak (which I did), but you can also make more Java-oriented versions, it's up to you how you want to design your program, the result will be more or less the same. This offers you a lot of flexibility in your design workflow.
Tip: search for "Jason internal actions" in the documentation to get a good description of the available AgentSpeak commands.
Also if you are interested in Jason, you might be interested in JaCaMo (= Jason + Cartago + Moise) which is the result of a cooperation of three projects authors to make a full-fledged cognitive agents framework which also can model complex environments (with artifacts theory) and multi-agents organisations (roles, groups, missions, etc.).
A last framework I know of but didn't have a chance to try is Mason which supports 2D and 3D environments. Never had a chance to try this one so I don't know how this compares with the others but you can try it out.
Here's a generic comparison.
http://www.duncanrobertson.com/research/AMLE.pdf
I had more or less the same problem a few months ago when I had to choose a framework for my simulation. I look at Repast, NetLogo, Swarm and Jade. NetLogo was nice and I tried to write some simple test applications but since I wanted to use Java as my programming language, NetLogo wasn't the best candidate. Repast has pretty much everything you need to write larger simulations and there are many projects (especially in social sciences) where Repast is used. My problems with Repasts were: bad API documentation, parameters that are passed to methods or constructers that are never used and don't make any sense at all (have a look at the source code) and a lot of boilerplate code. I'm using Jade (http://jade.tilab.com/) now and I'm really happy with it. The community is good and their mailing list is VERY active. Okay, Jade is just a library and a framework for agent-based modelling. You don't get anything like those visual editor in Repast and you'll have to write your own tool for visualising the results.
Cheers
You could simulate the traffic using a agent type called "packet" that will be spawned and send from a agent called "bot" to another agent called "bot" or "server". Instead of sending the packets to a IP address, you would be sending them to a pair of X and Y coordinates.
Netlogo has an example of how a virus spreads in a network, this might be a good starting point.
I have never tried NetLogo, but have I tried Repast-J and Simphony. It seems Simphony is good, but at the moment I am stuck at changing the Edge type from straight line to curved one. There is not enough documentation and examples available. Once I tried Mason which is based on java, too. It is similar to Repast-J, yet it was faster. But recently there is not much development in Mason. I would like to try out Jade later.
If you can already code in Java, you can also look at the following paper for a comparison between RePast, Swarm, Quicksilver, and VSEit, different freely available programming libraries for support of social scientific agent based computer simulation
Tobias, Robert, and Carole Hofmann. "Evaluation of free Java-libraries for social-scientific agent based simulation." Journal of Artificial Societies and Social Simulation 7.1 (2004).
Repast is definitely more flexible than NetLogo but the documentation is not very detailed for RePast Symphony
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