1. Emergence in Artificial Societies Evolving Communication and Cooperation in a Sugarscape world by Pieter Buzing

2. Plan What are ‘artificial societies’? Sugarscape Our goal: communication and cooperation Our model: VUScape Setup Results Conclusions

3. Artificial Society? Multi agent system –2 levels: autonomous parts, behaviour of whole –AS: more control over agents and world Artificial life –emergent behaviour –AS: important role for individual Agent based simulation –AS: no “problem to solve”, like optimization Social modeling –interactions of agents; effects individual goals on population

4. Sugarscape Epstein & Axtell, 1996 Torus shaped world: 50 x 50 cells Sugar resources [0 - 4] Agents looking for food Evolution

5. Sugarscape Agent “Internals” Age [0 - 100] Vision [1 - 6] Sugar Amount [0 - inf] Metabolism [1 - 4] Gender [m/f] Agent Actions Die Move Harvest Metabolise Reproduce

6. Sugarscape Reproduction rule Agent has gender: male or female Metabolism and vision are genetic! Parents: X Child:,, or Child inherits half of parents’ sugar

7. Sugarscape Agents will tend to move towards sugarhills Agents with high vision are better off Agents with low metabolism are better off

8. Our Goal Individual: –limited harvesting capabilities (maxSugarHarvest) –ability to talk and listen Emergent behaviour: –cooperation –communication “If cooperation is needed then talking is beneficial and communication will emerge”

9. VUScape Had to implement own testbed: VUScape Model is highly based on SugarScape The major changes: –Sugar randomly distributed; multi-agent cells –talkPref [0 - 1] and listenPref [0 - 1] genes –Talk actions and Listen actions –MaxSugarHarvest value: cooperation threshold

10. VUScape: random landscape Instead of 2 sugar hills a random distribution 2,500 sugar units are spread across 2,500 cells 30% population drop; but still viable world (because it is harder to find food?)

11. VUScape: limited vision range Vision range set to 1 instead of gene range [1-6] Evolution of vision is not the aim of our project local info from vision, global from communication Short-sighted agents face a tough environment

12. VUScape: multiple agents Cooperation scheme requires multi-agent cells Higher population size is now possible

13. VUScape: re-seed sugar Agents find food, wait there until it regenerates We need agents that are constantly searching Explorativeness is increased by reseeding sugar after consumption

14. VUScape: sex recovery period To avoid possible birth explosions we implement a sex recovery period Recovery period of 5 yields pop decrease of 11% Flattens the age distribution

15. Step 1: in need of help IF localAmount > maxSugarHarvest THEN inNeedOfHelp

16. Step 2: talking IF inNeedOfHelp AND rand < talkPref THEN communicate to others on x and y axis: –cell coordinates and sugar value

17. Step 3: listening IF rand < listenPref THEN listen to others on x and y axis

18. Step 4: cooperating Use obtained information in movement decision. Two agents can conquer any pile! Cooperation is beneficial for both parties. Communicative agents have an advantage?

19. Setup Stepwise increase cooperative pressure and monitor the communicative gene values. Experiment A: no communication –Talk and listen genes disabled Experiment B: with communication –Talk and listen genes initiated between 0 and 1 If communication is beneficial then an increase of talk and listen values is expected.

20. Results: no communication

21. Results: with communication

22. Results: listenPref

23. Results: talkPref

24. Conclusion Communication makes society more viable High talking and listening preferences give agents a selective advantage Higher cooperative pressure induces communication Future work: other topologies, communication protocols