Emergence in Artificial Societies
Evolving Communication and
Cooperation in a Sugarscape world
by Pieter Buzing
Plan
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What are ‘artificial societies’?
Sugarscape
Our goal: communication and cooperation
Our model: VUScape
Setup
Results
Conclusions
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
Sugarscape
• Epstein & Axtell, 1996
• Torus shaped world:
50 x 50 cells
• Sugar resources [0 - 4]
• Agents looking for
food
• Evolution
Sugarscape
Agent “Internals”
Agent Actions
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Age [0 - 100]
Vision [1 - 6]
Sugar Amount [0 - inf]
Metabolism [1 - 4]
Gender [m/f]
Die
Move
Harvest
Metabolise
Reproduce
Sugarscape
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Reproduction rule
Agent has gender: male or female
Metabolism and vision are genetic!
Parents: <m, v> X <M, V>
Child: <m,V>, <M,v>, <m,v> or <M,V>
Child inherits half of parents’ sugar
Sugarscape
• Agents will tend to move towards sugarhills
• Agents with high vision are better off
• Agents with low metabolism are better off
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”
VUScape
• Had to implement own testbed: VUScape
• Model is highly based on SugarScape
• The major changes:
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Sugar randomly distributed; multi-agent cells
talkPref [0 - 1] and listenPref [0 - 1] genes
Talk actions and Listen actions
MaxSugarHarvest value: cooperation threshold
VUScape: random landscape
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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?)
VUScape: limited vision range
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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
VUScape: multiple agents
• Cooperation scheme requires multi-agent cells
• Higher population size is now possible
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
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
Step 1: in need of help
IF localAmount > maxSugarHarvest
THEN inNeedOfHelp
Step 2: talking
IF inNeedOfHelp AND rand < talkPref
THEN communicate to others on x and y axis:
– cell coordinates and sugar value
Step 3: listening
IF rand < listenPref
THEN listen to others on x and y axis
Step 4: cooperating
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Use obtained information in movement decision.
Two agents can conquer any pile!
Cooperation is beneficial for both parties.
Communicative agents have an advantage?
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.
Results: no communication
Results: with communication
Results: listenPref
Results: talkPref
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