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How to use Trustworthy Agent Simulation: what you can do with it

An auditable, configurable LLM multi-agent town simulation built on AgentScope and Mesa, with replay, policy experiments and a local Streamlit dashboard.

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What do you want to do?

5 use cases

  • Run the default town and inspect it in the dashboard

    Run the 18-resident town offline and browse its map, contracts, cash and event audit.

    View prompt
    In the apromisedland/trustworthy-agent-simulation repo, set up the environment as the README Linux section describes, then run configs/town.yaml into runs/demo. Report the number of ticks committed and the path of the output folder. Verify that runs/demo contains run.sqlite, events.jsonl, metrics.csv and run.json.

  • Replay a saved run at a chosen tick

    Load a committed snapshot from a finished run and inspect the world at one tick.

    View prompt
    In the apromisedland/trustworthy-agent-simulation repo, replay the run at runs/demo for tick 10 using the project interpreter in .venv. Report the state summary for that tick. Verify that the replay command does not call any model or contact the network.

  • Compare policy interventions across shared seeds

    Run the policy suite on fixed seeds and read means, errors and 95% intervals.

    View prompt
    In the apromisedland/trustworthy-agent-simulation repo, run the policy batch suite with seeds 11,22,33 into runs/policies. Report the mean and 95% interval for each condition from the batch outputs. Verify that a single-seed result is not presented as an interval, since the README says one run does not yield one.

  • Run the public-goods scenario plugin

    Run the second plugin scenario to see how a scenario can extend the town without runner changes.

    View prompt
    In the apromisedland/trustworthy-agent-simulation repo, run configs/public_goods.yaml into runs/public-goods using the project interpreter. Report the output folder contents and the final tick. Verify that the run completes without editing any file under src.

  • Run the smoke scenario with a real model and budget cap

    Send real provider requests in LLM mode while staying under the default request and token budget.

    View prompt
    In the apromisedland/trustworthy-agent-simulation repo, check that TASS_API_KEY, TASS_BASE_URL and TASS_MODEL are set in .env without printing the key, then ask the user to confirm before running configs/smoke.yaml in --mode llm into runs/llm-smoke. Report the number of requests and tokens used against the default budget of 500 requests, 1,000,000 input tokens and 100,000 output tokens. Verify that the run stops at the last committed state if the budget is exhausted.

Quick start with Trustworthy Agent Simulation

  1. Check you have what it needs: Python 3.12 or 3.13 installed, with access to the python3.12 command on Linux; A terminal opened at the repository root; Internet access to install locked dependencies with uv.
  2. Open apromisedland/trustworthy-agent-simulation on GitHub and read the README and license.
  3. Run python3.12 -m venv .venv
  4. Run .venv/bin/python -m pip install uv==0.12.20
  5. Run .venv/bin/uv sync --frozen --extra dev --inexact
  6. Run .venv/bin/python -m tass.cli run --config configs/town.yaml --output runs/demo

These steps come from our top use case, Run the default town and inspect it in the dashboard, which also has a copy-paste agent prompt.

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About this repo

Requirements

  • Python 3.12 or 3.13 installed, with access to the python3.12 command on Linux
  • A terminal opened at the repository root
  • Internet access to install locked dependencies with uv
  • For real model runs only: an API key and a Chat Completions compatible endpoint with tool calling

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Questions about Trustworthy Agent Simulation

What is Trustworthy Agent Simulation?

An auditable, configurable LLM multi-agent town simulation built on AgentScope and Mesa, with replay, policy experiments and a local Streamlit dashboard. It is an open-source project on GitHub: https://github.com/apromisedland/trustworthy-agent-simulation.

Who is Trustworthy Agent Simulation for?

Researchers and developers who want to run, inspect, replay or compare synthetic town simulations, with or without a real model.

What can I do with Trustworthy Agent Simulation?

5 use cases so far, for example: Run the default town and inspect it in the dashboard; Replay a saved run at a chosen tick; Compare policy interventions across shared seeds. Each has steps and a copy-paste agent prompt.

What do I need to run Trustworthy Agent Simulation?

Python 3.12 or 3.13 installed, with access to the python3.12 command on Linux; A terminal opened at the repository root; Internet access to install locked dependencies with uv; For real model runs only: an API key and a Chat Completions compatible endpoint with tool calling.

What are alternatives to Trustworthy Agent Simulation?

Other hot AI repos in Research: Kaas, By2 KB, Md2 HD, Loci, LT2 MD.

Is Trustworthy Agent Simulation safe to run?

Deduped does not own, audit or vouch for it. Read the README and license, run it on your own systems first and review every command before you run it.