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Social Simulation

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Articles that would need better linking together:

Concepts

  • Artificial Moral Agents (That term seems almost exclusively used in the context of Machine ethics, though I could swear I saw it used in the context of norm simulations)
  • Normative agent, which might mean pretty much the same thing, but is used in the context of norm simulation.

Reciprocity

Topics

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Social simulations have been used to investigate a wide variety of topics:

  • Social norms: Robert Axelrod has used simulations to investigate the foundation of morality [1] An evolutionary approach to norms (PDF)]; others have modeled the emergence of norms using memes, using memes[2], or how social norms and emotions can regulate each other[3]. See [4] for an overview of the recent (as of 2008) research.
  • The origin of Institutions, by investigating under what conditions agents manage to coordinate[5], or by modeling the works of Robert Putnam on civic traditions[6]
  • Reputation, for example by making agents with a model of reputation from Pierre Bourdieu (image, social esteem, and prestige) and observing their behavior in a virtual marketplace[7].
  • Elections: Kim (2011) has modeled a psychological model of judgement from previous research (notably featuring motivated reasoning), and compared the statistical regularities of the simulation with empirical observations of voter behavior[9]; others have compared delegation methods[10][11].

Technologies

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(or, models used) (types of model)

  • Genetic algorithms
  • Agents on a grid
  • Cellular automata

(Rough notes)

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Economics should be one huge thing in here; models have been used in economics for a long time: see Economic model, as well as Computational economics and Agent-based computational economics.

  • Norms: Axelrod, (that state of the art paper), different approaches: Game Theory (Axelrod), Cognitive AI (Castelfranchi)
    • Specific norms: reciprocity
    • Norm internalization (as opposed to coercion)
  • Stereotyping and group reputation
  • Segregation
  • Language
  • Institutions

Model vs. Simulation

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Causal structure vs. observables? Two facets of the same thing?

A model tries to reproduce the causal structure as the scientist believes it to be. It's supposed to be predictive.

A simulation is more about superficial features, like fractal landscapes.

a discussion about that: "it is saying that the dyanmical model is not really any more causal that the simulation in the case of modeling organisms. That is is no better a model, and in fact because it tries to hard it may even be worse. Experiment bears this out, as currently the statistical models of ecosystem patterns actually seem to out-perform the supposedly dynamical/causal ones. In other words, given that we really don't know enough about the causalities to model them, it is better to model some more general aspect of the system, using fewer assumptions and fewer parameters subject to error."

Distinguishes two kinds of models:

  • Statistical
  • Causal / dynamic

Simulations, with varying parameters, are more about best/worst case estimates.

"The non-linear mathematical approach itself seems to be no more than a simulation, i.e., an instrumentalism (matching exercise between equation and natural behavior with no underlying causal theory). My sense is that because of the existence and importance of this deep level of organizational causality (pardon the invention of new terms), Rosen is then saying that everything model we currently have is really a simulation, even though many scientists humored themselves into thinking they were dealing with causalities. My own view is that Rosen's point is a good one, but a bit too harsh for many honest scientists who know their limits."

(on what a simulation is?) it "seems to be any representation of a natural system over time that is not constructed on sub-models of causalities, ie. generally thought of as the processes (efficient causes). However, it is quite subjective to decide when a model has taken into account enough causalities to qualify as a prediction." From here

Other source: "A part of the systems school sees qualitative modeling as a satisfactory way toapproach problems; while others see (quantitative) simulation necessary to achievethe rigorousness of scientific work. "

Other: "Traditionally, forming large models of systems has been via a mathematical model, which attempts to find analytical solutions to problems and thereby enable the prediction of the behavior of the system from a set of parameters and initial conditions. [...]

Note that the term computer simulation is broader than computer modeling, which implies that all aspects are being modeled in the computer representation."

History

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Dispersed between articles (also, all surprisingly recent)

Books

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People

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Intermediate

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More general stuff on morality


Worth putting somewhere: distinction between Goals and Interests; maybe more generalized concept of "interest":

May be relevant in Decision Analysis.

The discussion of known and unknown interests by Castelfranchi is pretty darn interesting. It ties into:

  • The Marxist concept of False Consciousness
  • A way to integrate learning, coordination and norms
  • Adaptive beliefs
  • Changing one's utility function
  • Conflict between short term and long term interests (learning to value long term interests)

"Utility Scientists (Luce and Raiffa 1990) hold a harmonious view of agents interests." in summary, unitary interest = individual, conflicting interests = group.

(And some discussion of interest adoption, tutorial roles - that is pertinent for FAI)

Machine Ethics

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Machine Ethic / Friendly AI

Books of note

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    • Cited by 2001 Flordi, Luciano and Sanders, J.W. "On the Morality of Artificial Agents", presented at Computer Ethics: Philosophical Enquiries, Dec 2001. (uses term Artificial Moral Agent)
  • SKYRMS B. 1996. Evolution of the Social Contract. Cambridge University Press, Cambridge.
    • "Pereira & Saptawijaya (2007) looks like it has some interesting stuff discussion on implementing morality, in "Modelling Morality with Prospective Logic"

People

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From a review: "Other essays are by philosophers, concerning the nature of rationality and morality, many of which are by some of the most well known philosophers in their fields: Michael Bratman, Paul Churchland, David Gauthier, Edward McClennen, Brian Skyrms and Eliot Sober are among the more famous names."

Peter A. Danielson

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homepage, author of a couple of books above. From University of British Columbia, Centre for Applied Ethics.

"My theoretical interest is to use modeling methods – agent-based computational methods from cognitive science, evolutionary game theory from economics and biology – better to understand how moral and ethical agents interact with social norms to solve (and create) problems. "

on UBC researcher list:

"Areas of specialization include ethical theory, cognitive science, applied ethics (environment and technology). Recent publications include Artificial Morality (Routledge, 1992), "Evolutionary Models of Cooperative Mechanisms: Artificial Morality and Genetic Programming," in Modelling Rationality, Morality and Evolution, ed. Peter Danielson (Oxford, 1998) and "Evolution and the Social Contract," Canadian Journal of Philosophy (1998). His main interest is in the development of evolutionary computer models to supplement and replace rational choice and traditional ethical theories."


Worked on Your Views, which looks interesting.

Nice list of papers here.

Norms and reciprocity

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Some overlap:

Reciprocity actually has that problem a bit more:

This paper has a nice summary on the sociologucal study of norms:

The statistical conceptualization of norms originates in behaviourism. A behavioural pattern becomes a norm if the majority of actors in fact behave due to this pattern. Thus, norms are objectively observeable and measureable. From this perspective any regular behaviour becomes a norm. One cannot distinguish between regular and rule-obeying behaviour, or conditioned and rule-obeying behaviour, or sanction-avoiding and rule-obeying behaviour. Examples of this approach are the theories of the formation of social norms by Sherif (1967) and Geiger (1962).
The theories of action of Durkheim, Weber, and Parsons represent the 'sociological' conceptualization of norms. According to Durkheim norms are social facts which can be identified through the mere existence of certain sanctions (1965: 112). The sanction does not constitute the norm, it is the symbol of it 'and as this symbol has the great advantage of being objective, accessible to observation and even to measurement, it is a good method to prefer it to the thing it represents' (Durkheim 1966: 426). Durkheim does not deny the reality of a subjective perspective on norms, but he promotes the methodological principle that scientists should choose the perspective of an objective observer. It was Weber (1960) who made explicit the difference between objectively observed behaviour and subjectively intended action. There are behavioural regularities which are based on practice (customs or tradition), on similar interest (market behaviour), and on notions of legitimate order. It is constitutive of normative action that the actor perceives behavioural rules as obliging or representative (1960: 26). In Parson's theory (1964) norms represent institutionalized role expectations. The objective character of norms is guaranteed by the integration of role expectations into the cultural system, its subjective character by internalization.
Ethnomethodologists deny the overall relevance of the sociological conceptualization of norms. According to Garfinkel (1967) there is not such a thing as a general norm which is independent of concrete context conditions. There are only situation specific expectations of concrete interaction partners which are actively negotiated by both sides. It is then the question how individuals constitute a common world. Ethnomethodologists have discovered several basic rules which have a pseudo-normative character. They are seen as obliging, and deviations are sanctioned. But they are not equivalent to sociological norms: they are far more deeply rooted in sociality, and are not amenable to reflection. Deviation from these basic rules is judged in clinical, not moral categories. Furthermore, 'a society's members know the moral order as perceivedly normal courses of action' (Garfinkel 1967: 35), i.e., in concrete interactions actors resort to the statistical conceptualization of norms.
Finally, developmental psychologists have put forward an ethical conceptualization of norms. Piaget and Kohlberg (1969, 1971) reconstruct the development of the moral consciousness of man. At any time, a subject is actively structuring and reflecting his/her social environment. Throughout his/her moral development three main stages can be distinguished: at the first stage of preconventional morality a child conforms to norms in order to avoid punishment - this corresponds to behaviourism; at the second stage of conventional morality a subject conforms to norms because he/she has internalized the norms of his family, peer group, or society - this corresponds to Parson's view; at the third, and final stage of postconventional morality a subject conforms to norms because of insight into abstract principles that allow for the foundation and justification of norms - this corresponds to the ethical conceptualization of norms. At this stage the subject is able to distinguish between statistical norms, 'sociological' norms, and ethical norms.

That is Harold Garfinkel.


references

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<references>

  1. ^ Robert Axelrod (1986): [www-personal.umich.edu/~axe/Axelrod%20Norms%20APSR%201986%20(2).pdf An Evolutionary Approach to Norms]
  2. ^ Felix Flentge, Daniel Polani and Thomas Uthmann (2001) Modelling the Emergence of Possession Norms using Memes
  3. ^ Alexander Staller and Paolo Petta (2001): Introducing Emotions into the Computational Study of Social Norms: A First Evaluation
  4. ^ Martin Neumann (2008): Homo Socionicus: a Case Study of Simulation Models of Norms
  5. ^ José Castro Caldas and Helder Coelho (1999): The Origin of Institutions: socio-economic processes, choice, norms and conventions
  6. ^ Dan Miodownik, Britt Cartrite and Ravi Bhavnani (2010): Between Replication and Docking: "Adaptive Agents, Political Institutions, and Civic Traditions" Revisited
  7. ^ Christian Hahn, Bettina Fley, Michael Florian, Daniela Spresny and Klaus Fischer (2007) : Social Reputation: a Mechanism for Flexible Self-Regulation of Multiagent Systems
  8. ^ JASSS vol. 14: Special section: Simulating the Social Processes of Science
  9. ^ Sung-youn Kim (2011): A Model of Political Judgment: An Agent-Based Simulation of Candidate Evaluation
  10. ^ Ramzi Suleiman and Ilan Fischer (2000) When One Decides for Many: The Effect of Delegation Methods on Cooperation in Simulated Inter-group Conflicts
  11. ^ Marie-Edith Bissey, Mauro Carini and Guido Ortona (2004) [jasss.soc.surrey.ac.uk/7/3/3.html ALEX3: a Simulation Program to Compare Electoral Systems]