Examining Leadership Dynamics in Agent Based Modeling

1. By Alex McGuigan Examining Leadership Dynamics in Agent Based Modeling

2. Purpose/Goal • Explore leadership dynamics in Sugarscape • Analyzing leadership traits in combat • Ultimate goal to discover what leadership trait is most attractive to followers • What leadership trait forms the most successful groups

3. Scope • Use Sugarscape as a base • Add a more complete system of combat and traits • Same simplistic, interconnected style as Sugarscape • Intelligence = Vision • Strength = Metabolism • Wealth = Sugar

4. Metabolism Sugar consumed per turn Strength Higher metabolism increases effectiveness in combat Strong agents have a harder time gathering Traits • Vision • Sight, obviously • Intelligence • Evaluation of others • Lower vision underestimates strength of enemy

5. Traits • Sugar • Food • Groups are food sharing • Advantage for group gathering • High metabolism agents fed by low metabolism group members, protects them in return • Morale • Has been scrapped

6. Combat • The equation: Metabolism * 4 + Sugar • Agents drop 2 sugar when they die in combat • Agents will move to the highest value sugar spot they can see, sugar at site + 2 if there is another agent there • Agents don't seek combat specifically, only seek highest concentration sugar • Agents don't attack agents that they know are stronger

7. Combat • If the highest value sugar spot is occupied, check to see if the occupant is stronger • Your combat vs. theirs, tie to defenders • Vision influences this, low vision underestimates their strength • Your combat vs. their combat * Vision/4 • Vision maxes at four, 4 vision has perfect perception, 1 vision attacks nearly indiscriminately • If your's is perceived as higher, attack • Run combat formula, tie to defenders, loser dies, winner gains 2 sugar

8. Group Dynamics • Decentralized groups, emerge spontaneously • What motivates them to form groups? • Groups are beneficial, food sharing, shared vision • Group advantages to gathering? • Group combat?

9. Group Dynamics • Who will be the leader? • Highest Sugar person? • Highest total stats? • First member? • Leader advantages • Select new members – vision based • Limited command over group?

10. Design • MASON version of Sugarscape • Test by placing agents of random traits in Sugarscape, see what happens • No randomness inside actual mechanics • Simplicity is the goal

11. Development • Combat dynamic coded • Large series of difficult bugs remain in system of sugar and occupant detection • Group dynamic largely planned • Traits implemented, group functionality partly coded

12. Results • Robert Axtell, one of the two creators of Sugarscape approves of the project • Actual testing is held up by aforementioned bugs