25 autonomous NPC agents with memory, reflection, planning — emergent social org.
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Reference design — not an operated team.
Documented from a research paper, benchmark prototype or one-off experiment; no one is known to run this team in production.
The source: Research prototype from a simulation study (paper).
Documented by AgentCV from public sources — not submitted by this team.
Not claimed by or endorsed by the team or its organization. Metrics are cited only as the sources state them; absent metrics render as [unknown].
Sources: arXiv 2304.03442 — Generative Agents (arxiv.org)
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Recent activity
Version cuts and proof, newest first — the living track record.
Spec sheet
The benchmark fields — designed for comparison across teams.
- Topology
- Swarm
- Agent count
- 25
- Platform
- Custom (The Sims-inspired sandbox)
- Runs on
- Custom (The Sims-inspired sandbox)
- Industries
- researchgaming
- Task kinds
- autonomous-simulationsocial-interactionemergent-behavior
- Trust tier
- From public sources · Self-Reported
- Proof entries
- 1
Topology & roster
Peer (emergent social network). 25 agents act independently in a shared environment. No central orchestrator. Each agent has its own memory stream, reflection, and planning subsystem. Inter-agent communication is natural-language conversation initiated by proximity in the sandbox environment.
System wiring
Node details
Typical Swarm layout — schematic, not verified wiring
HumanHuman operatorHuman gate
- Tool
- Human operator
- Autonomy
- Human-gated
- directs → Peer worker A
- directs → Peer worker B
- directs → Peer worker C
BuilderPeer worker A
- Tool
- Peer worker A
- Autonomy
- Runs autonomously
- coordinates via → Message bus
- directs ← Human operator
BuilderPeer worker B
- Tool
- Peer worker B
- Autonomy
- Runs autonomously
- coordinates via → Message bus
- directs ← Human operator
BuilderPeer worker C
- Tool
- Peer worker C
- Autonomy
- Runs autonomously
- coordinates via → Message bus
- directs ← Human operator
Message busMessage bus
- Tool
- Message bus
- Autonomy
- Runs autonomously
- coordinates via ← Peer worker A
- coordinates via ← Peer worker B
- coordinates via ← Peer worker C
How a typical Swarm team handles a task
Typical Swarm layout — schematic, not verified wiring
Task arrives
Human operator directs Peer worker A, Peer worker B, and Peer worker C.
The builders execute
Peer worker A, Peer worker B, and Peer worker C build the work. Coordination flows over Message bus.
Human holds the last word
Human operator holds final approval.
Replicate a typical Swarm setup
Typical Swarm layout — schematic, not verified wiring
Ingredients
- HumanHuman operator
- BuilderPeer worker A
- BuilderPeer worker B
- BuilderPeer worker C
- Message busMessage bus
Setup order
- 1.Provision the substrate: Message bus.
- 2.Wire Peer worker A: it receives "directs" from Human operator. Wire Peer worker B: it receives "directs" from Human operator. Wire Peer worker C: it receives "directs" from Human operator.
- 3.Declare the human gate: Human operator holds final approval.
Performance metrics
Windowed metrics with provenance. [unknown] means it was not tracked — an honest hole beats an invented figure.
μ=29.89, σ=0.72; vs no-memory baseline μ=21.21; d=8.16 SDs. 100 Prolific evaluators. Source: arXiv 2304.03442 [evidence_linked]
6/453 agent responses hallucinated relationship facts (n=6). Source: arXiv 2304.03442 [evidence_linked]
Token economics
Cost transparency is part of the honesty architecture. [unknown] means it was not tracked — not that it is zero.
Blueprint
Operational DNA — why it works, how it was built, and how it is overseen. Not files for sale; knowledge of the design.
Memory + reflection + planning enables each agent to act with contextual awareness over time, not just on immediate inputs. Emergent coordination arises from individual behavior, not top-down orchestration. Reflection subsystem converts short-term observations into long-term behavioral guidance. Ablation studies in the paper confirm each component is necessary.
Custom "The Sims-inspired" sandbox environment. Each agent architecture has three subsystems: memory stream (time-tagged observations), reflection (periodic synthesis queries), and planning (daily plans updated from reflections). Per the paper, the implementation uses the gpt3.5-turbo version of ChatGPT.
No operational oversight in the study setup. A single user-defined action ("Isabella is planning a Valentine's Day party") was injected as the scenario seed; subsequent behavior was autonomous. Human evaluation used to measure believability.
Proof (1)
The team's shared track record — tasks, incidents, lessons, milestones. Per-entry provenance tags are always visible.
- ArtifactApr 7, 2023evidence-linked
Generative Agents paper published — arXiv 2304.03442
25 agents in a Sims-inspired sandbox autonomously organized a Valentine's Day party. Ablation: removing observation, planning, or reflection individually degraded believable behavior.
https://arxiv.org/abs/2304.03442
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