CS382:Unit-compsoc - Revision history

Nate: /* Comments */

2009-04-27T14:25:50Z

Comments

← Older revision		Revision as of 14:25, 27 April 2009
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	* <font color="blue">This lab seems kind of short as compared with the other ones, which isn't necessarily a bad thing. However, if you wanted to move it to a prelab in order to have more time to do some sort of example or have them do something with Looking Around Corners as part of the lab, that might be good. On the other hand, you could also have them do some real life homework, like looking at the distribution of how people sit in Saga. Maybe they could find some environmental factors that influence students in Saga as well (ie people tend to sit closer to food?).</font>		* <font color="blue">This lab seems kind of short as compared with the other ones, which isn't necessarily a bad thing. However, if you wanted to move it to a prelab in order to have more time to do some sort of example or have them do something with Looking Around Corners as part of the lab, that might be good. On the other hand, you could also have them do some real life homework, like looking at the distribution of how people sit in Saga. Maybe they could find some environmental factors that influence students in Saga as well (ie people tend to sit closer to food?).</font>
	* <font color="darkmagenta">Agreed, I'm not sure this would fill up an entire 3 hours or however long labs are. Re: real life homework/observations: are people just people, or would we want them to account for gender, race, year, age, etc?</font>		* <font color="darkmagenta">Agreed, I'm not sure this would fill up an entire 3 hours or however long labs are. Re: real life homework/observations: are people just people, or would we want them to account for gender, race, year, age, etc?</font>
			* <font color="darkmagenta">How is it useful in these disciplines? etc~</font>

	== Lab Feedback ==		== Lab Feedback ==

Nate: /* Lecture Notes */

2009-04-27T14:25:12Z

Lecture Notes

← Older revision		Revision as of 14:25, 27 April 2009
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	* Lecture 3		* Lecture 3
	** Where is ABM useful? ~~<font color="darkmagenta">How is it useful in these disciplines? etc~</font>~~		** Where is ABM useful?
	*** Economics		*** Economics
	**** Economics is largely a science of local interactions - buyers and sellers, loaners and borrowers - that create a complex macrocosm.		**** Economics is largely a science of local interactions - buyers and sellers, loaners and borrowers - that create a complex macrocosm.

Dylanp at 18:27, 24 April 2009

2009-04-24T18:27:53Z

← Older revision		Revision as of 18:27, 24 April 2009
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	== Lab Feedback ==		== Lab Feedback ==
	*My only real issue with this lab is that isn't exactly so much a lab as a very interesting thought experiment. There should be some component of this lab that has them doing something and producing answers to questions with data and interpretation of that data at some point. The lab as it stands could definitely make a very good first chunk of a lab without too much change. The biggest change to make to what's already there would be to give more concrete deliverables. I found myself spending upwards of 3 hours on just this thought experiment because I had no idea what was an appropriate amount to write on each step. To make this lab complete past just that first part, there should be a second part that pushes them out of theory and into practice in one way or another.		*My only real issue with this lab is that isn't exactly so much a lab as a very interesting thought experiment. There should be some component of this lab that has them doing something and producing answers to questions with data and interpretation of that data at some point. The lab as it stands could definitely make a very good first chunk of a lab without too much change. The biggest change to make to what's already there would be to give more concrete deliverables. I found myself spending upwards of 3 hours on just this thought experiment because I had no idea what was an appropriate amount to write on each step. To make this lab complete past just that first part, there should be a second part that pushes them out of theory and into practice in one way or another.
			*I loved the first part of the lab. It was very fun to tweak the values in order to get the results that were desired. The questions were straightforward and easy to answer, but they still required a little bit of thought behind them, which I thought was a very nice touch. One thing to keep in mind with the section of the lab, however, is that what makes up a dystopia can be very subjective. My impression of it was that jail times would be long, there would be lots of police, and the police would have an overwhelming presence. This may not be an idea that other people share.
			*Another thing to point out is that it's not immediately obvious what the "visual range" toggle does. I was under the impression that it decreased the visible range of the agents themselves, making the rebellions take less long to spread. However, after some tampering with it, I'm positive that it dictates how far the cops can see, which has a factor in the "Risk calculation" that causes the agents to determine whether it is safe to rebel and therefore rebel. You might want to look into providing the students with a bit of information about the various controls and what they do. It doesn't have to be very in-depth, as I got the sense that part of the lab was figuring out what it does, but a little information might be nice.
			*This would probably take about an hour or two to do well, especially if some thought and deliberation were given to the questions. Otherwise, it wouldn't take very long at all. This would probably be a great way to tell apart those who put some time and effort into it from those who didn't care, actually.
	*Worked pretty well. The second part of the Lab gets the students thinking. Need to know a knowledge of agent-based modeling, so if the students didn't understand during the lectures, they will need to figure it out to complete this lab.		*Worked pretty well. The second part of the Lab gets the students thinking. Need to know a knowledge of agent-based modeling, so if the students didn't understand during the lectures, they will need to figure it out to complete this lab.
	[http://cs.earlham.edu/~purcebr/soc_cs382.txt Lab Write-up]		[http://cs.earlham.edu/~purcebr/soc_cs382.txt Lab Write-up]

Purcebr: /* Lab Feedback */

2009-04-24T14:22:58Z

Lab Feedback

← Older revision		Revision as of 14:22, 24 April 2009
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	== Lab Feedback ==		== Lab Feedback ==
	My only real issue with this lab is that isn't exactly so much a lab as a very interesting thought experiment. There should be some component of this lab that has them doing something and producing answers to questions with data and interpretation of that data at some point. The lab as it stands could definitely make a very good first chunk of a lab without too much change. The biggest change to make to what's already there would be to give more concrete deliverables. I found myself spending upwards of 3 hours on just this thought experiment because I had no idea what was an appropriate amount to write on each step. To make this lab complete past just that first part, there should be a second part that pushes them out of theory and into practice in one way or another.		*My only real issue with this lab is that isn't exactly so much a lab as a very interesting thought experiment. There should be some component of this lab that has them doing something and producing answers to questions with data and interpretation of that data at some point. The lab as it stands could definitely make a very good first chunk of a lab without too much change. The biggest change to make to what's already there would be to give more concrete deliverables. I found myself spending upwards of 3 hours on just this thought experiment because I had no idea what was an appropriate amount to write on each step. To make this lab complete past just that first part, there should be a second part that pushes them out of theory and into practice in one way or another.
			*Worked pretty well. The second part of the Lab gets the students thinking. Need to know a knowledge of agent-based modeling, so if the students didn't understand during the lectures, they will need to figure it out to complete this lab.
			[http://cs.earlham.edu/~purcebr/soc_cs382.txt Lab Write-up]

	== Josh Letter ==		== Josh Letter ==

Nate: /* Comments */

2009-04-23T21:15:21Z

Comments

← Older revision		Revision as of 21:15, 23 April 2009
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	* <font color="darkmagenta">These are very high-level... narrowing them down more will help a great deal. Also, how is the split made between the two+ classes?</font>		* <font color="darkmagenta">These are very high-level... narrowing them down more will help a great deal. Also, how is the split made between the two+ classes?</font>
	* <font color="red">I'd argue that they need to be expanded, that at a high level they cover the correct topics but need more depth to be useful.</font>		* <font color="red">I'd argue that they need to be expanded, that at a high level they cover the correct topics but need more depth to be useful.</font>
			* <font color="blue">This lab seems kind of short as compared with the other ones, which isn't necessarily a bad thing. However, if you wanted to move it to a prelab in order to have more time to do some sort of example or have them do something with Looking Around Corners as part of the lab, that might be good. On the other hand, you could also have them do some real life homework, like looking at the distribution of how people sit in Saga. Maybe they could find some environmental factors that influence students in Saga as well (ie people tend to sit closer to food?).</font>
			* <font color="darkmagenta">Agreed, I'm not sure this would fill up an entire 3 hours or however long labs are. Re: real life homework/observations: are people just people, or would we want them to account for gender, race, year, age, etc?</font>

	== Lab Feedback ==		== Lab Feedback ==

Nate: /* Bill of Materials */

2009-04-23T21:15:05Z

Bill of Materials

← Older revision		Revision as of 21:15, 23 April 2009
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	==== Bill of Materials ====		==== Bill of Materials ====
	Nada. Paper and pencil.		Nada. Paper and pencil.

	* <font color="blue">This lab seems kind of short as compared with the other ones, which isn't necessarily a bad thing. However, if you wanted to move it to a prelab in order to have more time to do some sort of example or have them do something with Looking Around Corners as part of the lab, that might be good. On the other hand, you could also have them do some real life homework, like looking at the distribution of how people sit in Saga. Maybe they could find some environmental factors that influence students in Saga as well (ie people tend to sit closer to food?).</font>
	* <font color="darkmagenta">Agreed, I'm not sure this would fill up an entire 3 hours or however long labs are. Re: real life homework/observations: are people just people, or would we want them to account for gender, race, year, age, etc?</font>

	== Evaluation ==		== Evaluation ==

Nate: /* Comments */

2009-04-23T21:14:21Z

Comments

← Older revision		Revision as of 21:14, 23 April 2009
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	* <font color="blue">A minimum number would be helpful here. People are lazy.</font>		* <font color="blue">A minimum number would be helpful here. People are lazy.</font>
	* <font color="blue">Where were the example applets??</font>		* <font color="blue">Where were the example applets??</font>
			* <font color="darkmagenta">These are very high-level... narrowing them down more will help a great deal. Also, how is the split made between the two+ classes?</font>
			* <font color="red">I'd argue that they need to be expanded, that at a high level they cover the correct topics but need more depth to be useful.</font>

	== Lab Feedback ==		== Lab Feedback ==

Nate: /* Lecture Notes */

2009-04-23T21:14:00Z

Lecture Notes

Nate: /* Lecture Notes */

2009-04-23T21:13:21Z

Lecture Notes

← Older revision		Revision as of 21:13, 23 April 2009
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	== Lecture Notes ==		== Lecture Notes ==
	~~<font color="darkmagenta">These are very high-level... narrowing them down more will help a great deal. Also, how is the split made between the two+ classes?</font>~~

	~~<font color="red">I'd argue that they need to be expanded, that at a high level they cover the correct topics but need more depth to be useful.</font>~~
	* Lecture 1		* Lecture 1
	** ~~What is Agent Based Modeling?~~		** Comp. Soc. begins with Axtell and Epstein.
	*** ~~Game~~ of ~~Life~~		*** They wanted to "...begin the development of a computational approach that permits the study of... [trade, migration, group formation, combat, interaction with an environment, transmission of culture, propagation of disease, and population dynamics] ...from an evolutionary perspective as a single social science, a transdiscipline subsuming such fields as economics and demography." (Epstein 2)
	*** Schelling's segregation model (as seen in [~~http://www~~.~~theatlantic~~.~~com/doc/200204/rauch Seeing Around Corners]~~)		** How is this new discipline implemented?
	*** Agents		*** Agents
	**** ~~internal~~ state		**** Internal state
	**** ~~behavioral~~ rules		**** Behavioral rules
	**** ~~some~~ static states (ie race), many influenced by environment according to rules (ie economic status, cultural identity) (~~Axtell~~ 4)		**** Some static states (ie race), many influenced by environment according to rules (ie economic status, cultural identity) (Epstein 4)
	*** Environment		*** Environment
	**** "Medium through which agents interact" eg topographic landscape or communication network (Axtell 5).		**** "Medium through which agents interact" eg topographic landscape or communication network (Axtell 5).
	**** Can be static or change over time (either through agents' actions or otherwise)		**** Can be static or change over time (either through agents' actions or otherwise)
	*** Rules		*** Rules
	**** Dictate what agents can do and what their environments can do; eg 'look around as far as you can, find the site richest in food, go there, eat the food' (~~Axtell~~ 5)		**** Dictate what agents can do and what their environments can do; eg 'look around as far as you can, find the site richest in food, go there, eat the food' (Epstein 5)
	**** Agent Environment rules (ie food collection)		**** Agent-Environment rules (ie food collection)
	**** Agent Agent rules (ie reproduction)		**** Agent-Agent rules (ie reproduction)
	*** Emergent Behavior
	**** As Axtell and Epstein state, "The defining feature of an artificial society model is...that fundamental social structures and group behaviors emerge from the interaction of individual agents operating on artificial environments under rules that place only bounded demands on each agen'ts information and computational capacity" (Axtell 6).
	**** Features like tribal formation and economic classes should naturally arise (Axtell 6)
	*** Micro simplicity -> macro complexity
	*** Ties to object oriented programming (high level, so as not to confuse) (Axtell 5)
	**** Encapsulation of internal state
	**** Procedures == agent's behavioral rules
	** What are its advantages and disadvantages?
	*** Advantages
	**** Can describe things through emergence that mathematical formulas can't
	**** Tend to require far less "wet" research
	**** Programming can be simple (using ABM frameworks)
	*** Disadvantages
	**** Sometimes too simple
	**** Don't always scale well

	* Lecture 2		* Lecture 2
			* Emergent Behavior
			** As Axtell and Epstein state, "The defining feature of an artificial society model is...that fundamental social structures and group behaviors emerge from the interaction of individual agents operating on artificial environments under rules that place only bounded demands on each agen'ts information and computational capacity" (Epstein 6).
			** Features like tribal formation and economic classes should naturally arise (Epstein 6)
			* The big idea?
			** That micro-simplicity leads to macro-complexity.
			*** Game of life
			*** Schelling and his original model (as seen in [http://www.theatlantic.com/doc/200204/rauch Seeing Around Corners])
			** Sugarscape model (Epstein 21-53)
			*** To demonstrate and explore their theories, Epstein and Axtell created the Sugarscape.
			*** It consists of a landscape with varying levels of resources called "sugar" and "spice" populated by randomly dropped agents who require the sugar to stay alive.
			*** The agents mate and reproduce if they can get enough food; otherwise they move about seeking new food sources.
			*** Agents are aware of their families
			*** Agents have a preference for either sugar or spice and are allowed to trade with one another (or borrow and lend).
			*** Agents are given rules for combat
			*** A&E witnessed the formation of tribes, economic classes, migratory patterns, and warfare.

			* Lecture 3
	** Where is ABM useful? <font color="darkmagenta">How is it useful in these disciplines? etc~</font>		** Where is ABM useful? <font color="darkmagenta">How is it useful in these disciplines? etc~</font>
	*** Economics		*** Economics
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	*** When attempting to model agent sets with high levels of heterogeneity		*** When attempting to model agent sets with high levels of heterogeneity
	**** A model of a rocket's trajectory, for example, could be represented as a series of agents - air molecules, rocket materials, units of power (thrust) - but the number of agents involved is far too high for this to be accomplished in any human-acceptable amount of time.		**** A model of a rocket's trajectory, for example, could be represented as a series of agents - air molecules, rocket materials, units of power (thrust) - but the number of agents involved is far too high for this to be accomplished in any human-acceptable amount of time.
	** Some Examples
			* Lecture 4
			** What are its advantages and disadvantages?
			*** Advantages
			**** Can describe things through emergence that mathematical formulas can't
			**** Tend to require far less "wet" research
			**** Programming can be simple (using ABM frameworks)
			*** Disadvantages
			**** Sometimes too simple
			**** Don't always scale well
			** Ties to object oriented programming (high level, so as not to confuse) (Axtell 5)
			*** Encapsulation of internal state
			*** Procedures == agent's behavioral rules
			** Some Examples - Sociology and otherwise
	*** [http://en.wikipedia.org/wiki/Boids Boids] Model of bird flocking.		*** [http://en.wikipedia.org/wiki/Boids Boids] Model of bird flocking.
	*** [http://www.cs.utk.edu/~mclennan/Classes/420-594-F07/NetLogo/Ants.html Ants] Model of ants' food collection habits		*** [http://www.cs.utk.edu/~mclennan/Classes/420-594-F07/NetLogo/Ants.html Ants] Model of ants' food collection habits
	*** [http://ccl.northwestern.edu/netlogo/models/run.cgi?Moths.718.474 Moths] Model of moths' love for light sources		*** [http://ccl.northwestern.edu/netlogo/models/run.cgi?Moths.718.474 Moths] Model of moths' love for light sources
			*** [http://ccl.northwestern.edu/netlogo/models/TrafficGrid Traffic Grid] Model of city-grid traffic
	* ~~Lecture 3~~		*** [http://ccl.northwestern.edu/netlogo/models/Scatter Scatter] Model of children's scattering tendencies
	** ~~Computational Sociology~~		*** [http://ccl.northwestern.edu/netlogo/models/Segregation Segregation] Recreation of Schelling's original segregation model
	*** Axtell and Epstein - ~~Growing Artificial Societies~~		*** [http://ccl.northwestern.edu/netlogo/models/Cooperation Cooperation] Model of cooperation / competition for resource
	**** They wanted to "...begin the development of a computational approach that permits the study of... [~~trade, migration, group formation, combat, interaction with an environment, transmission of culture, propagation of disease, and population dynamics]~~ ..~~.from an evolutionary perspective as a single social science, a transdiscipline subsuming such fields as economics and demography." (Axtell 2)~~
	*** Why?
	**** Perhaps distribute and discuss introductory materials from "Computational Sociology and Agent Based Modeling" article
	*** Example models~~, demo in class~~
	**** [http://~~www~~.~~cmol~~.~~nbi.dk~~/models/~~infoflow/infoflow.html Self Assembling~~ of ~~Information on networks]~~
	**** [http://~~jasss~~.~~soc~~.~~surrey.ac.uk~~/12/1/~~6/appendixB~~/~~EpsteinAxtell1996.html Sugarscape]~~

	* Lecture 4
	** case studies?
	** in depth example - netlogo. go through agent, agent movements, potential interactions --->should come earlier!
	** talk about policy + abm (link)

	== Lab 1 ==		== Lab 1 ==

Nate: /* Lecture Notes */

2009-04-22T21:30:00Z

Lecture Notes

← Older revision		Revision as of 21:30, 22 April 2009
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	*** Game of Life		*** Game of Life
	*** Schelling's segregation model (as seen in [http://www.theatlantic.com/doc/200204/rauch Seeing Around Corners])		*** Schelling's segregation model (as seen in [http://www.theatlantic.com/doc/200204/rauch Seeing Around Corners])
			*** Agents
			**** internal state
			**** behavioral rules
			**** some static states (ie race), many influenced by environment according to rules (ie economic status, cultural identity) (Axtell 4)
			*** Environment
			**** "Medium through which agents interact" eg topographic landscape or communication network (Axtell 5).
			**** Can be static or change over time (either through agents' actions or otherwise)
			*** Rules
			**** Dictate what agents can do and what their environments can do; eg 'look around as far as you can, find the site richest in food, go there, eat the food' (Axtell 5)
			**** Agent Environment rules (ie food collection)
			**** Agent Agent rules (ie reproduction)
	*** Emergent Behavior		*** Emergent Behavior
	*** ~~Simple Rulesets~~		**** As Axtell and Epstein state, "The defining feature of an artificial society model is...that fundamental social structures and group behaviors emerge from the interaction of individual agents operating on artificial environments under rules that place only bounded demands on each agen'ts information and computational capacity" (Axtell 6).
			**** Features like tribal formation and economic classes should naturally arise (Axtell 6)
	*** Micro simplicity -> macro complexity		*** Micro simplicity -> macro complexity
	*** Ties to object oriented programming (high level, so as not to confuse)		*** Ties to object oriented programming (high level, so as not to confuse) (Axtell 5)
			**** Encapsulation of internal state
			**** Procedures == agent's behavioral rules
	** What are its advantages and disadvantages?		** What are its advantages and disadvantages?
	*** Advantages		*** Advantages
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	** Where is it not useful?		** Where is it not useful?
	*** When attempting to model something that is simple at a high level and complex at a low level.		*** When attempting to model something that is simple at a high level and complex at a low level.
			*** When attempting to model agent sets with high levels of heterogeneity
	**** A model of a rocket's trajectory, for example, could be represented as a series of agents - air molecules, rocket materials, units of power (thrust) - but the number of agents involved is far too high for this to be accomplished in any human-acceptable amount of time.		**** A model of a rocket's trajectory, for example, could be represented as a series of agents - air molecules, rocket materials, units of power (thrust) - but the number of agents involved is far too high for this to be accomplished in any human-acceptable amount of time.
	** Some Examples		** Some Examples
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	** Computational Sociology		** Computational Sociology
	*** Axtell and Epstein - Growing Artificial Societies		*** Axtell and Epstein - Growing Artificial Societies
	**** They wanted to .. ~~citation~~ from pg 2 ~~of intro~~		**** They wanted to "...begin the development of a computational approach that permits the study of... [trade, migration, group formation, combat, interaction with an environment, transmission of culture, propagation of disease, and population dynamics] ...from an evolutionary perspective as a single social science, a transdiscipline subsuming such fields as economics and demography." (Axtell 2)
	*** Why?		*** Why?
	**** Perhaps distribute and discuss introductory materials from "Computational Sociology and Agent Based Modeling" article		**** Perhaps distribute and discuss introductory materials from "Computational Sociology and Agent Based Modeling" article

← Older revision		Revision as of 21:14, 23 April 2009
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	* Lecture 2		* Lecture 2
	* Emergent Behavior		** Emergent Behavior
	** As Axtell and Epstein state, "The defining feature of an artificial society model is...that fundamental social structures and group behaviors emerge from the interaction of individual agents operating on artificial environments under rules that place only bounded demands on each agen'ts information and computational capacity" (Epstein 6).		*** As Axtell and Epstein state, "The defining feature of an artificial society model is...that fundamental social structures and group behaviors emerge from the interaction of individual agents operating on artificial environments under rules that place only bounded demands on each agen'ts information and computational capacity" (Epstein 6).
	** Features like tribal formation and economic classes should naturally arise (Epstein 6)		*** Features like tribal formation and economic classes should naturally arise (Epstein 6)
	* The big idea?		** The big idea?
	** That micro-simplicity leads to macro-complexity.		*** That micro-simplicity leads to macro-complexity.
	*** Game of life		**** Game of life
	*** Schelling and his original model (as seen in [http://www.theatlantic.com/doc/200204/rauch Seeing Around Corners])		**** Schelling and his original model (as seen in [http://www.theatlantic.com/doc/200204/rauch Seeing Around Corners])
	** Sugarscape model (Epstein 21-53)		*** Sugarscape model (Epstein 21-53)
	*** To demonstrate and explore their theories, Epstein and Axtell created the Sugarscape.		**** To demonstrate and explore their theories, Epstein and Axtell created the Sugarscape.
	*** It consists of a landscape with varying levels of resources called "sugar" and "spice" populated by randomly dropped agents who require the sugar to stay alive.		**** It consists of a landscape with varying levels of resources called "sugar" and "spice" populated by randomly dropped agents who require the sugar to stay alive.
	*** The agents mate and reproduce if they can get enough food; otherwise they move about seeking new food sources.		**** The agents mate and reproduce if they can get enough food; otherwise they move about seeking new food sources.
	*** Agents are aware of their families		**** Agents are aware of their families
	*** Agents have a preference for either sugar or spice and are allowed to trade with one another (or borrow and lend).		**** Agents have a preference for either sugar or spice and are allowed to trade with one another (or borrow and lend).
	*** Agents are given rules for combat		**** Agents are given rules for combat
	*** A&E witnessed the formation of tribes, economic classes, migratory patterns, and warfare.		**** A&E witnessed the formation of tribes, economic classes, migratory patterns, and warfare.

	* Lecture 3		* Lecture 3