Is it possible to connect two separate nodes by two links? - netlogo

I am wondering if it is possible to do this as I am trying to build a traffic simulation model and may need to utilise this feature , should it exist, in my model.

There two, and only two, conditions under which a pair of turtles may be connected by more than one link:
If the links are directed, you can have two links, going in opposite directions.
If the links are different breeds.
You might consider alternatives like having a single link but adding a links-own variable to the links containing a weight, count, or other information.

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Modelling agent behaviour, where single agent operates under two conditions simultaneously

Any tips on how to model agent behaviour in an environment where two sets of rules apply simultaneously.
Specifically, what I am looking to simulate is a situation where an Agent operates under a specific set of rules, such as an employee-employer relationship, but at the same time, operates on perhaps different "informal" rules, such as an employee-employee relationship. Effectively there are two network structures in place, but the agent operates in both structures.
Any example models out there that I could take a look at?
(This is a model design question, not programming, so it probably belongs on the NetLogo user group instead of here.)
My colleague and I wrote a book on modeling decisions that are tradeoffs between competing objectives, in ABMs. It's focus is on ecology but the concepts could be useful for you.
The basic idea is to come up with an objective function that includes both "sets of rules" as you call them. Perhaps something like maximizing your relations with fellow employees without getting fired by the employer. Then build very simple models of how decisions affect the mechanisms that drive co-worker relations, probability of getting fired, etc. It's not simple, but it's very powerful and flexible. You won't find a simple approach that's very general.
The fun part is trying different variations and comparing how they work.
https://press.princeton.edu/books/paperback/9780691195285/modeling-populations-of-adaptive-individuals
Maybe I’m under-thinking this, but..I would encode both (all) sets of rules, and have the agent execute those rules as appropriate.
So, how to choose and execute rules?
Per social interaction:
Execute one behavior randomly based on which relationships are present
Choose one or more behaviors, as #1 and execute all of them in a specific order
As above, but execute behaviors in random order
For all possible behaviors, assign a probability based on whatever factors (number of role-members present, utility, consequence, etc l) Choose and execute one behavior randomly based on that probability (roulettes-wheel selection)
Choose more than one… execute in fixed or random order
Proportionate to the value of a “social-competence” property, Select a number of possible behaviors as #4. Then randomly select one of those to execute.
Here’s a code-segment example of #6
;; list of possible reactions
;; these are variables or reporters that report
;; an anonymous command that executes the behavior
Let action-list (list
boss-action
employee-action
coworker-action
peer-action
)
;; measure social situation
;; list of values from reporters
;; these are reporters that return a value
;; based on, for example, how many of that type of
;; relationship are present.
Let choice-list ( list
( probability-of-doing-boss-behavior )
( probability-of-employee-behavior )
( probability-of-coworker-behavior )
( probability-of-peers-behavior )
)
;; think about situation, choose possible actions,
;; as many times as social-competence allows.
;; roulette-wheel should return the index of the selected action
Let reaction-list (n-values social-competence
[ -> roulette-wheel choice-list ] )
;; choose an action from those options
Let action-index one-of reaction-list
;; execute that action
Run item action-index action-list
The same result as a single combined objective function might be a physics type model where the result of any single set of rules is a vector of some strength pushing ("nudging"?) the agent in some direction. Then you could have as many sets of rules as you want, each contributing it's own vector of force, and the final result would be a resultant combined net force and subsequent Newtonian F=m*a or rearranging acceleration = ( vector sum of forces )/mass.
I'm trying to imagine how I respond when the expectations of different groups I belong to clash, and whether a linear sum vector model describes it. I recall in college when I couldn't resolve Catholic support for the Vietnam War and "Kill for Christ" was a tongue-in-cheek slogan. I think in that case the "forces" didn't cancel out -- they resulted in ABANDONING membership in one of the groups to reduce cognitive dissonance. So, not a linear sum of zero in that case.
Another unstable human approach might be to keep going back and forth when two forces attempting to dominate behavior conflict -- first going with one a few steps then feeling guilty and going the other way a few steps. So which one dominates at any given step might depend on one's recent path and history and which one you "owed" something to. Or imagine being married to two people and trying to keep both of them happy. Maybe you partition space and Monday-Tuesday-Wednesday you keep one happy and Thursday-Friday-Saturday you keep the other happy and Sunday you go fishing.

Define agent population which is dispersed in specific areas or divided in groups?

I have one agent (100 population) in main. Is it possible to divide this population into several groups, separated from each other but still connected?
There was a solution where we can define this population in another agent (containing square fields), but we need not have this dependency over another agent. I hope there will be a solution.
Thank you for help.
Sure. Many different options, depends on what you want to do with them.
Easiest is to use a parameter within your Agent type, maybe "gender". Create an OptionList "availableGenders" with entries like "FEMALE" and "MALE".
Then, when creating your agents, you can assign each a gender via that parameter.
Now, you have 1 population of humans but you can easily filter them by gender (using findAll(myPopulation, a -> a.gender.equals(MALE)) or similar)
Lots of example models use this approach, please check them to understand how it is done.

Identify crossroad nodes in openstreetmap data (.pbf)

does anybody know if there is a way I can seperate only the crossroad nodes which are included in a .pbf file? Is this clue (if a node is crossroad or not) included in this file's format?
Another option to solve your issue would be to use the new Atlas project.
As part of loading .osm.pbf files into in-memory Atlas files, it takes care of doing way sectioning on roads:
Load your pbf file into an Atlas. You will then have an Atlas object that you could save to a file and re-use.
Use the Atlas APIs to access all the intersections
In the end, each Atlas Node which is connected to more than 4 Edges on a two-way road or 2 Edges on a one way road would be a candidate if I understand your question correctly.
I'm not aware of a ready-made solution for this task, but it should still be relatively easy to do.
For parsing the .pbf file, I recommend using an existing library like Osmosis or Osmium. That way, you only need to implement the actual semantics of your use case.
The nodes themselves don't have any special attributes that mark them as crossroads. So instead, you will have to look at the ways containing the nodes.
Some considerations when implementing this:
You need to check the way's tags to find out whether it's a road. The most relevant key for that is highway. The details depend on your specific use case – for example, you need to decide whether footways, forestry tracks, driveways, ... should count.
What matters is the number of connecting way segments at a node, not the number of ways. For example, a node that is part of two ways may be a crossroads (if at least one of the ways continues beyond that node), or may not (if both ways start/end at that node).

Generating sub-systems based on user input (MATLAB/SimMechanics)

The user in this webinar;
http://www.mathworks.com.au/videos/parameterizing-bodies-68850.html?form_seq=conf1134
can create new levels of links for the scissor lift by copy pasting the sub systems.
I was wondering if there was any way the number of subsystems and the joints could be automated via user input.
i.e a gui which allows the user to input the number of levels in the scissor lift and that number of levels (subsystems) is generated in SimMechanics.
If someone could provide a solution I could adapt it to the problem I'm trying to solve.
Thanks in advance!
Yes, you can automate it, as long as you know what susbsytems and what joints you want to add. The functions of interest are:
add_block(path_to_your_subsystem,path_to_destination_subsystem) (I assume your susbsystem is stored in a library). You probably want to specify the 'Position` parameter so that all blocks don't end up on top of each other. It will take some experimenting to find coordinates that work for your model and that are parameterised based on the number of susbystems to add.
add_line(path_to_subsystem_of_interest,path_to_output_port,path_to_input_port). You'll need to know which port you want to connect to which and figure out how many times you need to do this based on the number of subsystems to add. Simscape and SimMechanics are a special type of ports, and you need to refer to them correctly otherwise it won't work, see Programatically connect two subsystems for more details (note: this is undocumented as far as I know and is therefore likely to change in a future release).
So in short, yes it's possible (I've done it in the past), but it's by no means easy. See this blog for a very simple introduction.

How can I cluster short messages [Tweets] based on topic ? [Topic Based Clustering]

I am planning an application which will make clusters of short messages/tweets based on topics. The number of topics will be limited like Sports [ NBA, NFL, Cricket, Soccer ], Entertainment [ movies, music ] and so on...
I can think of two approaches to this
Ask users to tag questions like Stackoverflow does. Users can select tags from a predefined list of tags. Then on server side I will cluster them based on tags.
Pros:- Simple design. Less complexity in code.
Cons:- Choices for users will be restricted.
Clusters will not be dynamic. If a new event occurs, the predefined tags will miss it.
Take the message, delete the stopwords [ predefined in a dictionary ], apply some clustering algorithm on the stemmed message to make a cluster and depending on its popularity display the cluster. The cluster will be displayed till the time it remains popular [ many messages/minute].New messages will be skimmed and assigned to corresponding clusters.
Pros:- Dynamic clustering based on the popularity of the event/accident.
Cons:- Increased complexity. More server resources required.
I would like to know whether there are any other approaches to this problem. Or are there any ways of improving the above mentioned methods?
Also suggest some good clustering algorithms.I think "K-Nearest Clustering" algorithm is apt for this situation.
Check out Carrot2, this tool extracts the tags from the text and clusters. You can download it from here and check the algorithms implemented (Lingo, mainly) here.
Hope this help you.
Use Bayesian classification. Train the filter with some predefined corpus, and (optionally) provide a way for users to further refine it by flagging things that were incorrectly categorized.
Here's some examples of using the Bayesian classifier in NLTK.
I am also doing a similar kind of thing. I think hashtags are a good way if you are talking specifically about twitter. You could also perform some classification but it should be enriched with some external knowledge base like Wikipedia etc.
Anyways, if your solution is better, please post it here