1 / 18

Playing Evolution Games in the Classroom

Playing Evolution Games in the Classroom. Colin Garvey GK-12 Fellow. 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.

sian
Télécharger la présentation

Playing Evolution Games in the Classroom

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Playing Evolution Games in the Classroom Colin Garvey GK-12 Fellow

  2. 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?

  3. 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

  4. 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

  5. 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

  6. Get that paper, son

  7. Hawk

  8. Hawk vs Hawk • Brutal battle leaves one hawk triumphant, and one poor hawk gravely injured • Winner = 50 points • Loser = - 100 points

  9. Dove

  10. 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

  11. 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

  12. HOW TO PLAY THE GAME

  13. Fight! Let’s

  14. 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?

  15. The Payoff Matrix

  16. 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-ishnessdepends on the payoff and thus on (environmental) initial conditions

  17. Fight!

  18. 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)

More Related