Week 13 Discussion Questions

COMPILED WEEK 13 QUESTIONS: GAME THEORY

 

Overall

There are many reasons that models, even incorrect ones, may be useful. Some of the reasons we have discussed include developing hypotheses, gaining insight into mechanisms of a system, and opening up new ways of conceptualizing a system. Each has a different approach, and offers different suggestions for application. What is the usefulness of the models in each of this week’s readings? Do the suggestions for application match the strengths and capacity of the models?

 Santos et al.

In the communities modeled in this study, is information about cooperation assumed to be 100% transparent for everyone involved or do only neighbors communicate?

What is a working definition of social diversity espoused by Santos et al.? How does that match up with a definition of social diversity used more colloquially? Might social diversity be relevant for only certain types of PGGs?

Are there other ways of thinking about diversity? How might this translate into social-economic systems?

Santos, Santos, and Pacheco address a crucial omission in PGGs—that of complexity and feedbacks in social networks. However, their model seems to assume that actors are still (mostly) acting in self-interest. Is this a necessary prerequisite for these kinds of games, or can scenarios be devised in which people can explicitly consider community-level benefits?

Do you thing that the scenarios of absence of reputation and punishment and compulsory participation are valid in social communities?

How might different shapes and configurations of networks (discussed two weeks ago) affect these findings?

In real-world strategy development, it seems like repeated interaction is a primary mechanism for building trust, alliances and cooperative agreement. Games must be simplified, but is this oversimplification?

How do we evaluate the validity and potential applications of such a limited, constrained and unrealistic game?

Do the results of this study imply anything in particular for international relations and climate change mitigation negotiations, where representatives of whole neighborhoods/networks would talk?

What do the mechanisms for interaction in the game replicate from real-world interactions? In the game, an individual adopts a strategy of a randomly chosen neighbor (if more fit) with a probability proportional to the fit difference). Is this replicating trust-building and alliance formation, or is it just replicating honest communication with an acquaintance?

In discussing game outcomes, the authors describe that defectors induce a negative feedback loop (p. 214 pg 6). Is this common in PGG? The feedback loop seems to be self-generated rather than designed. Are there ways to determine these loops prior to game or policy implementation in order to either avoid or enhance them, depending on desired outcomes?

Which is the limit between the evolution between cooperators and defectors? When the network will be saturated? Which is the role of the defectors in the transmission of information in the network? Could be related the negative feedback of the defectors with chaos in the network?

In Santos et al., it seems as if there is almost a catastrophic shift in going from few cooperators to many cooperators. Does this suggest there is always a tipping point in PGGs, and what does this mean for global warming?

How do the defectors reach their demise, and is it truly accurate that their self-annihilation is consistent across different PGGs? For instance, I would think that a scarcity of resources would promote the demise of defectors in a game where they are competing for goods, whereas an abundance would not have nearly the same effect.

Hasson et al.
By framing the game in terms of a ‘climate change’ game, are the authors introducing bias based on the players’ perceptions of the real-world climate change debate?

Is the discrete trade-off between mitigation and adaptation telling or just unrealistic? How would a half-and-half option have changed the game (i.e allowing players to equally divide their contribution between mitigation and adaptation)? The authors argue that they were exploring preferences, but aren’t there shades of gray?

Are there better, more intuitive and readable, ways to describe a payoff matrix?

How to decide between playing the game with real people versus running a computer simulation? How do the computer simulations replicate the real people’s decision-making patterns (just via probabilities) and is this valid? How does the choice of your subjects (young college students in South Africa) affect the outcomes of your game?

The game theory models strike me as useful in that they make some of the explicit trade-offs visible (at least to the modeler), via the cohice of parameters. However, the idea that complex social and policy bodies will react similarly to individual college students seems like a great oversimplification. Is there something qualitatively different about applying simple deterministic models to social systems than to ecological ones?

Hasson et al. acknowledge there is no uniform way to measure an investment in adaptation. Does this pose a problem at all for how trade-offs can be realistically balanced against each other?

How realistic or applicable is this work because participants in the experiment did not have the option of ‘doing nothing’? In reality, it seems like many countries are doing a great job of doing nothing about climate change mitigation.

I agree with the question the authors themselves raise about whether or not we can carry over results from individuals “playing the game” to a country level application. What are the potential pitfalls of equating the implications of results?

Might the scale at which adaptation (local efforts) or mitigation (enforced by national standards) takes place be an important factor to consider in trade-off analysis? Is it possible this study just wasn’t designed to address these trade-offs? How might it be done better? If we need both types of efforts to address climate change, as the authors suggest, then what is the utility of pitting the two against each other in this game structure?

Do you think that adaptation will be a strategy of addressing climate change or a consequence of climate change? In the same way do you thing that international carbon market (e.g. sequestration of carbon in forest outside that made C emission) is a good way to mitigate climate change?

Do you think that the results of this paper could be applied as an analogy of the world countries?

Table 5 shows that individual and socio-economical characteristics have no significant impact in the treatments, but can be this an analogy of the countries in the world (considering: surface, political influences, level of information on environmental concerns, economic develop, etc.)?

Are the attitudes of cooperation an emergent pattern?

Is validation a meaningful goal for this type of model? How realistic does a model need to be for it to be useful? Is accuracy important?

If there is no difference in the high vulnerability vs. low vulnerability mitigation fraction in Hasson, what sort of rhetoric could improve the willingness of countries to cooperate?

Also, how realistic is this model, given that countries tend to cluster in alliances when promoting climate change-related initiatives?

Allesina and Levine
What requirements are necessary for intransitive networks to emerge?

What are the pros and cons of the simulation versus analytical approach used here?

A tournament! Can competitive sports and betting strategies tell us something about species diversity (and vice versa)? Species diversity seems much more complex, but basketball fans might disagree.

Could the competitive network framework that prevents an even number of co-existing species help explain the trophic levels in an ecosystem (i.e. green world/brown world)? Why is this dichotomy occurring, does it depend on the number of limiting factors or the structure of intransitivies?

What might happen if limiting factors were weighted based on their global impact, i.e. temperature rise? How much can you increase the complexity of the game before it becomes impossible to analyze the results?

It’s interesting that the coexisting species are characterized by a neutral stable equilibrium. Is this related to the Nash equilibrium that’s discussed in game theory? Is it possible to create a game that mimics thresholds where perturbation might result in some alternative stable state rather than hovering around an average density equal to the equilibrium value?

Would spatial heterogeneity combine with intransitivity to interactively favor diversity maintenance even where a heterogeneous environment is degraded compared to a more homogenous non-degraded system?

“With enough limiting factor the sp richness could be a constant fraction of the total sp pool’ do you consider this result usefull to predict natural succession or ecosystem restoration management?

In which ecosystems could you applied this theory?

Do you consider that is better have five limiting factors than one? What is the relation between the Law of the Minimum (Liebig) and the results of this Allesina and Levine?

Are the mature forest ecosystems still having a fraction of the total sp richness?

How the network competitive theory is related with the hysteresis of the natural system?

“The general agreement between the theory and common community patterns suggests that the abundance and diversity patterns generated by our model are not so inconsistent with nature to justify its rejection. But this leaves unanswered the key question of whether intransitive networks of competitive ability stabilize coexistence in real communities.” What is the required threshold for validation? What kind of data would be necessary to explore the application of this model? Is this feasible?

How realistic are zero-sum games?

What are some examples of rock-paper-scissors dynamics in nature?

How do the results of the rock-paper-scissors model differ from PGGs? Do you see a dramatic shift from one dominant competitor to another, or is there a more stable equilibrium (it notes “species cycle with a temporal average density equal to their equilibrium value”, but I don’t think that that says a lot about how the species oscillate)?

 


Comments

Week 13 Discussion Questions — 6 Comments

  1. Santos et al.
    1. In real-world strategy development, it seems like repeated interaction is a primary mechanism for building trust, alliances and cooperative agreement. Games must be simplified, but is this oversimplification?

    1. What do the mechanisms for interaction in the game replicate from real-world interactions? In the game, an individual adopts a strategy of a randomly chosen neighbor (if more fit) with a probability proportional to the fit difference). Is this replicating trust-building and alliance formation, or is it just replicating honest communication with an acquaintance?

    2. How do we evaluate the validity and potential applications of such a limited, constrained and unrealistic game?

    3. In discussing game outcomes, the authors describe that defectors induce a negative feedback loop (p. 214 pg 6). Is this common in PGG? The feedback loop seems to be self-generated rather than designed. Are there ways to determine these loops prior to game or policy implementation in order to either avoid or enhance them, depending on desired outcomes?

    Hasson et al.
    1. By framing the game in terms of a ‘climate change’ game, are the authors introducing bias based on the players’ perceptions of the real-world climate change debate?

    2. Is the discrete trade-off between mitigation and adaptation telling or just unrealistic? How would a half-and-half option have changed the game (i.e allowing players to equally divide their contribution between mitigation and adaptation)? The authors argue that they were exploring preferences, but aren’t there shades of gray?

    3. Are there better, more intuitive and readable, ways to describe a payoff matrix?

    4. How to decide between playing the game with real people versus running a computer simulation? How do the computer simulations replicate the real people’s decision-making patterns (just via probabilities) and is this valid? How does the choice of your subjects (young college students in South Africa) affect the outcomes of your game?

    Allesina and Levine
    1. A tournament! Can competitive sports and betting strategies tell us something about species diversity (and vice versa)? Species diversity seems much more complex, but basketball fans might disagree.

    2. Could the competitive network framework that prevents an even number of co-existing species help explain the trophic levels in an ecosystem (i.e. green world/brown world)? Why is this dichotomy occurring, does it depend on the number of limiting factors or the structure of intransitivies?

    3. What might happen if limiting factors were weighted based on their global impact, i.e. temperature rise? How much can you increase the complexity of the game before it becomes impossible to analyze the results?

    4. It’s interesting that the coexisting species are characterized by a neutral stable equilibrium. Is this related to the Nash equilibrium that’s discussed in game theory? Is it possible to create a game that mimics thresholds where perturbation might result in some alternative stable state rather than hovering around an average density equal to the equilibrium value?

  2. Week 13

    Santos et al. 2008
    Social diversity promotes the emergence of cooperation in public goods games

    • What is a working definition of social diversity espoused by Santos et al.? How does that match up with a definition of social diversity used more colloquially? Might social diversity be relevant for only certain types of PGGs?
    • Do the results of this study imply anything in particular for international relations and climate change mitigation negotiations, where representatives of whole neighborhoods/networks would talk?

    • In the communities modeled in this study, is information about cooperation assumed to be 100% transparent for everyone involved or do only neighbors communicate?

    Allesina & Levine 2011
    A competitive network theory of species diversity

    • What requirements are necessary for intransitive networks to emerge?

    • What are the pros and cons of the simulation versus analytical approach used here?

    • Would spatial heterogeneity combine with intransitivity to interactively favor diversity maintenance even where a heterogeneous environment is degraded compared to a more homogenous non-degraded system?

    Hasson et al. 2010
    Climate change in a public goods game: Investment decision in mitigation
    versus adaptation

    • Hasson et al. acknowledge there is no uniform way to measure an investment in adaptation. Does this pose a problem at all for how trade-offs can be realistically balanced against each other?

    • How realistic or applicable is this work because participants in the experiment did not have the option of ‘doing nothing’? In reality, it seems like many countries are doing a great job of doing nothing about climate change mitigation.

    • I agree with the question the authors themselves raise about whether or not we can carry over results from individuals “playing the game” to a country level application. What are the potential pitfalls of equating the implications of results?

    • Might the scale at which adaptation (local efforts) or mitigation (enforced by national standards) takes place be an important factor to consider in trade-off analysis? Is it possible this study just wasn’t designed to address these trade-offs? How might it be done better? If we need both types of efforts to address climate change, as the authors suggest, then what is the utility of pitting the two against each other in this game structure?

  3. Sorry for the short reply this week–it is an extra busy one.

    Reviva Hasson a, Åsa Löfgren b,⁎, Martine Visser a
    The game theory models strike me as useful in that they make some of the explicit trade-offs visible (at least to the modeler), via the cohice of parameters. However, the idea that complex social and policy bodies will react similarly to individual college students seems like a great oversimplification. Is there something qualitatively different about applying simple deterministic models to social systems than to ecological ones?
    Social diversity promotes the emergence of cooperation in public goods games
Francisco C. Santos1, Marta D. Santos2 & Jorge M. Pacheco2
    Santos, Santos, and Pacheco address a crucial omission in PGGs—that of complexity and feedbacks in social networks. However, their model seems to assume that actors are still (mostly) acting in self-interest. Is this a necessary prerequisite for these kinds of games, or can scenarios be devised in which people can explicitly consider community-level benefits?

    How might different shapes and configurations of networks (discussed two weeks ago) affect these findings?

  4. Santos et al 2008
    Which is the limit between the evolution between cooperators and defectors? When the network will be saturated? Which is the role of the defectors in the transmission of information in the network? Could be related the negative feedback of the defectors with chaos in the network? Do you thing that the scenarios of absence of reputation and punishment and compulsory participation are valid in social communities?

    Allesina and Levine 2011
    “With enough limiting factor the sp richness could be a constant fraction of the total sp pool’ do you consider this result usefull to predict natural succession or ecosystem restoration management? In which ecosystems could you applied this theory? Do you consider that is better have five limiting factors than one? What is the relation between the Law of the Minimum (Liebig) and the results of this Allesina and Levine? Are the mature forest ecosystems still having a fraction of the total sp richness? How the network competitive theory is related with the hysteresis of the natural system?

    Hasson et al 2010
    Do you think that adaptation will be a strategy of addressing climate change or a consequence of climate change? In the same way do you thing that international carbon market (e.g. sequestration of carbon in forest outside that made C emission) is a good way to mitigate climate change? Do you think that the results of this paper could be applied as an analogy of the world countries? Table 5 shows that individual and socio-economical characteristics have no significant impact in the treatments, but can be this an analogy of the countries in the world (considering: surface, political influences, level of information on environmental concerns, economic develop, etc.)? Are the attitudes of cooperation an emergent pattern?

  5. There are many reasons that models, even incorrect ones, may be useful. Some of the reasons we have discussed include developing hypotheses, gaining insight into mechanisms of a system, and opening up new ways of conceptualizing a system. Each has a different approach, and offers different suggestions for application. What is the usefulness of the models in each of this week’s readings? Do the suggestions for application match the strengths and capacity of the models?

    Allesina and Levine: “The general agreement between the theory and common community patterns suggests that the abundance and diversity patterns generated by our model are not so inconsistent with nature to justify its rejection. But this leaves unanswered the key question of whether intransitive networks of competitive ability stabilize coexistence in real communities.” What is the required threshold for validation? What kind of data would be necessary to explore the application of this model? Is this feasible?

    Santos et al.: Are there other ways of thinking about diversity? How might this translate into social-economic systems?

    Hasson et al.: Is validation a meaningful goal for this type of model? How realistic does a model need to be for it to be useful? Is accuracy important?

  6. 1. In Santos et al., it seems as if there is almost a catastrophic shift in going from few cooperators to many cooperators. Does this suggest there is always a tipping point in PGGs, and what does this mean for global warming?

    2. How do the defectors reach their demise, and is it truly accurate that their self-annihilation is consistent across different PGGs? For instance, I would think that a scarcity of resources would promote the demise of defectors in a game where they are competing for goods, whereas an abundance would not have nearly the same effect.

    3. How realistic are zero-sum games?

    4. What are some examples of rock-paper-scissors dynamics in nature?

    5. How do the results of the rock-paper-scissors model differ from PGGs? Do you see a dramatic shift from one dominant competitor to another, or is there a more stable equilibrium (it notes “species cycle with a temporal average density equal to their equilibrium value”, but I don’t think that that says a lot about how the species oscillate)?

    6. If there is no difference in the high vulnerability vs. low vulnerability mitigation fraction in Hasson, what sort of rhetoric could improve the willingness of countries to cooperate? Also, how realistic is this model, given that countries tend to cluster in alliances when promoting climate change-related initiatives?

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