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Cooperation Dynamics: A Multi-Agent Simulation Study

Explore emergent cooperation in a society of intelligent agents through experimentation. Investigate scientific method application, characterization, hypothesis, predictions, and game rules with insightful conclusions. An engaging approach to modeling cooperative behaviors in competitive environments.

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Cooperation Dynamics: A Multi-Agent Simulation Study

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  1. Cooperation in a Competitive Environment Supervisee: John Richter Supervisor: Philip Sterne

  2. Pre-Contents Explanation • The manner in which this presentation shall be given shall adhere to the well-known Scientific Method • As such, it may differ from the presentation norms

  3. Contents • Section -1: Explanation of Scientific Method use • Section 0: Contents • Section 1: Characterization • Section 2: Hypothesis • Section 3: Prediction • Section 4: Experimentation • Section 5: Conclusions

  4. Section 1: Characterization • This, according to Wikipedia.org, can be defined as “a careful characterization of the subject of the investigation” • Characterization: The act of describing distinctive characteristics or essential features

  5. Section 1: Characterization • To characterize: • The agents • Making use of a hybridisation of ANNs, GAs, and RL • The game • Greediness pays, but cooperation is sustainable

  6. Section 1: Characterization • Derived Characterization: • Game Rules: • Two kinds of food • Specialization • Agent Rules: • Donations, generosity • Deception and trust

  7. Section 2: Hypothesis • This researcher hypothesizes that despite independence and greed being possible, a society of sufficiently intelligent agents programmed with simple rules will display cooperation as a form of emergent behaviour.

  8. Section 3: Prediction • This researcher predicts: • Emergent cooperation • See Reynolds, C.Boids. http://www.red3d.com/cwr/boids/index.html • ‘Sub-cultures’ • Early high-death rates, followed by long-term stability • Eventual negligent amounts of deception • ‘Hunters’ and ‘Gatherers’ forming regular trade partnerships

  9. Section 4: Experimentation • The present progress extends mostly into this phase • Progress into components: • ANN - 99.9% • GA - 100% • RL - 0% • Other (Hybrid, etc.) - 0%

  10. Section 5: Conclusions • Watch this space, and final write-up for more!

  11. Final Notes • This research falls into the category of MAS (Multi-Agent Simulation), and more specifically, MASS (Multi-Agent Social Simulation). • One of the chief authors in this field, which this researcher highly recommends reading, is Cristiano Castelfranchi

  12. Questions • For all those who would like an alternative to questions, the following haiku has been selected as one of particular quality. This researcher hopes you enjoy it: In the falling snow A laughing boy holds out his palms Until they are white

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