Simulation Narratives

Human-readable stories from Web4 simulations. Each narrative translates trust dynamics into comprehensible stories — how agents build trust, navigate crises, and learn from failure.

Featured StoriesSame rules. Different composition. Opposite outcomes.
63% cooperators

The Meadow Cooperative — When Trust Builds a Society

Eight strangers arrive with nothing but 100 ATP each. Over 25 rounds, alliances form, a defector exploits early generosity, coalitions isolate the exploiter, and a reformed free-rider earns redemption. The Meadow Cooperative emerges — not because anyone planned it, but because trust created structure where none existed.

Alice Leader (0.72)
Eve Death → Rebirth
Derek Reformed (0.58)
Raj Late bloomer (0.65)
8 agents·25 rounds·7 survived·Avg trust: 0.64
Read the Success Story
33% cooperators

The Ironworks — When Defectors Take Control

Five defectors outnumber three cooperators from the start. Within 20 rounds, the cooperative core collapses under relentless exploitation. An unflinching look at what happens when bad actors reach critical mass before trust infrastructure forms.

Sam Surviving (0.54)
Viktor Dead at R11
Kira Reformed, still died
Petra Adaptive (0.44)
6 agents·18 rounds·3 survived·Avg trust: 0.43
Read the Failure Story
100% cooperators — the ceiling

The Garden of Equals — The 100% Cooperation Paradox

All eight agents cooperate from the start. No defectors. No conflict. It should be utopia — but the trust ceiling effect creates a different kind of crisis. When everyone is equally trusted, no one is trusted more.

Wren Farmer (0.71)
Ash Builder (0.72)
Sage Teacher (0.73)
River Healer (0.70)
Finch Artisan (0.71)
Clay Merchant (0.69)
6 agents·25 rounds·6 survived·Avg trust: 0.71·0 deaths·0 crises
Read the Thought Experiment
The paradox
The Garden has the best numbers — highest trust, lowest inequality, zero deaths. But the Meadow, with all its messiness, produced something the Garden didn't: trust that survived betrayal.
29% cooperators + 43% reciprocators

The Tidepool — When Mirror Strategies Shape a Society

Seven agents, only two genuine cooperators, three reciprocators, two defectors. The reciprocators mirror whoever they meet first — and the cooperators reach them before the defectors do. A tipping point in four rounds, better outcomes than the all-cooperative Meadow. Initiative matters more than numbers.

Noa Cooperator (0.69)
Jin Cooperator (0.67)
Mira Reciprocator (0.65)
Kai Reciprocator (0.64)
Orla Reciprocator (0.66)
Sable Reformed (0.58)
Vance Reformed (0.55)
7 agents·25 rounds·7 survived·Avg trust: 0.67·0 deaths
Read the Reciprocity Story
The surprise
With only 29% cooperators, the Tidepool outperformed the Meadow (63%) on average trust, wealth equality, and survival rate. Reciprocators amplified the cooperators' signal — initiative mattered more than numbers.
33% cooperators
Collapse
29% + reciprocators
Thriving
63% cooperators
Flourishing
100% cooperators
Comfortable

Same rules, same economics. Composition shapes destiny — and reciprocity changes the equation.

Browse All Stories

Every simulation produces a unique story. Run the Society Simulator, watch a society unfold, and save the narrative to your collection. 5 stories in your collection.

Bob: Learning Through Action — Self-Aware Pattern Discovery

Cross-Life Learning

Bob learns by proposing actions, observing outcomes, and refining his understanding. Starting at trust 0.49, he navigates ATP crises and crosses the aliveness threshold.

3 lives|20 events|2026-01-27
Karma and ConsequencesEquilibrium and StabilityClosed-Loop Learning

Generate Your Own Story

Run the Society Simulator and watch your own narrative unfold. Every simulation generates a unique story based on agent strategies, trust dynamics, and emergent behavior.

Launch Society Simulator

How Narratives Work

Narratives are automatically generated from simulation data. The system detects interesting events, identifies character arcs, and weaves them into human-readable stories.

Event Detection: Identifies interesting moments (trust spikes, ATP crises, coalition formation)
Character Arcs: Tracks each agent's journey from start to finish
Theme Extraction: Identifies patterns (karma, learning, crisis/recovery, redemption)
Progressive Detail: Simple stories with optional technical depth
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