Playing Evolution Games in the Classroom Colin Garvey GK-12 Fellow.
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Transcript of Playing Evolution Games in the Classroom Colin Garvey GK-12 Fellow.
![Page 1: Playing Evolution Games in the Classroom Colin Garvey GK-12 Fellow.](https://reader036.fdocuments.in/reader036/viewer/2022062421/56649ca35503460f949628d5/html5/thumbnails/1.jpg)
Playing Evolution Games in the Classroom
Colin GarveyGK-12 Fellow
![Page 2: Playing Evolution Games in the Classroom Colin Garvey GK-12 Fellow.](https://reader036.fdocuments.in/reader036/viewer/2022062421/56649ca35503460f949628d5/html5/thumbnails/2.jpg)
Why don’t lions eat lions?
• Lions compete with other animals for space on the savanna, but they surely compete most with other lions – overlap of needs is highest.
• If individual selfishness is the overriding strategy, why don’t conspecifics overwhelmingly target one another for destruction?
• Cannibalism does happen but why isn’t it the norm?
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The central problem of evolution
• Individual organisms’ needs overlap most with others of their own species
• How does cooperation evolve in a cut-throat environment of selfish individuals?
• Altruism is the “central problem” for modern evolutionary theory– It is locally disadvantageous, so how can it evolve
in a system wherein each system change must be more fit (adaptive) than before
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Modeling the real world
• How can selfish gene theory explain the altruistic “gloved fist of nature”?– Economic cost/benefit analysis in terms of
individual energy expenditure (over time)– Turns out that for A to kill B actually helps their
mutual enemy C, who benefits by losing a potential threat free of energetic cost
– The conditions of social life amongst selfish individuals can still lead to the evolution of altruistic behavior and the formation of groups
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Strategies for living in the real world
• Consider an idealized account of an interaction between two organisms of the same species, X– They are in competition for some resource, R– In their encounter, they have behavioral options:
• Fight or Flight reactions are modeled as
– Hawk & Dove strategies• The dynamics of these two idealized strategies
can tell us something about the evolution of behavior
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Get that paper, son
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Hawk
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Hawk vs Hawk
• Brutal battle leaves one hawk triumphant, and one poor hawk gravely injured– Winner = 50 points– Loser = - 100 points
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Dove
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Dove vs Dove
• Lots of posturing, feinting, stare-downs• Eventually, single winner emerges with 50 pts• Loss of time, but no one physically hurt• Thus both players lose 10 points– Winner = (50 – 10) = 40– Loser = -10
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Hawk vs Dove / Dove vs Hawk
• Hawks always win because• Doves quit immediately, avoiding injury and
loss of time– Winner = Hawk = 50 points– Loser = Dove = 0 points
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HOW TO PLAY THE GAMEMy Play Opponent Outcome Total
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Fight!
Let’s
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Average Payoff
• The average payoff for any player depends on the strategies of other players
• What is the average payoff for a population of – All hawks? – All doves? – 50/50 mix?
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The Payoff Matrix
Dove vs Dove
Lots of posturing, but no one hurt
Winner: 50 – 10 = 40Loser = -10
Hawk vs Hawk –
Loser is seriously injured
Winner = 50Loser = -100
Hawk vs Dove
Dove quits immediately; Hawk wins
Winner = 50Loser = 0
Dove vs Hawk
Dove quits immediately; Hawk wins
Winner = 50Loser = 0
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Evolutionary Stable Strategies
• Imagine if cach individual can play either Hawk or Dove each time– Simple pattern-based strategies will be outwitted
• An important question is then if one can do better than random by playing some optimal combination of Hawk and Dove strategies– The optimal ratio of hawk/dove-ishness depends
on the payoff and thus on (environmental) initial conditions
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Fight!
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Conclusions• Evolution in Action• Cost/benefit Analysis• Optimization of Goal Oriented Behavior (GOB)
Future Directions• Computer Simulations• Incorporate an Understanding of Heredity• Family Trees• Exploring “Relatedness” (in a broader context)