Start building on Google Cloud with $300 in free credits. No commitment, no credit card required until you're ready to scale.
Launch your next project with $300 in free Google Cloud credits—no strings attached. Test, build, and deploy without risk. Use your credits across the entire Google Cloud platform to find what works best for your needs. After your credits are used, continue with always-free tier services. Only pay when you're ready to scale. Sign up in minutes and start exploring.
Start Free Trial
$300 Free Credits to Build on Google Cloud
New to Google Cloud? Get $300 in credits to explore Compute Engine, BigQuery, Cloud Run, Gemini Enterprise Agent Platform, and more.
Start your next project with $300 in free Google Cloud credit. Spin up VMs, run containers, query petabytes in BigQuery, or build agents with Gemini Enterprise Agent Platform. Once your credits are used, keep building with 20+ always-free tier products including Compute Engine, Cloud Storage, GKE, and Cloud Run functions. No commitment required—just sign up and start building.
RegMAS (Regional Multi Agent Simulator) is a spatially explicit multi-agent model framework, developed in C++ language and designed for long-term simulations of effects of government policies over agricultural systems (farm sizes, incomes, land use..).
TOAST (Trust Organisational Agent System Testbed) is a simulation framework used to evaluate and compare different trust models for agents embedded in organisational systems.
EMSIM -- EnergyMarketSIMulator -- Agent-based EEX Replay. EMSIM is a META-Simulator that can show you what would have happened at the EEX spot market if ...
This project is A Mitochondrial OxydoReduction Simulation System. It consists of two linked projects: a program for displaying and analysing large biomolecular systems (Floral) and a multi-agent simulator for biomolecular oxydoreduction systems (AMORSS).
Agent-based Grid simulator built on top of Repast simulation engine. Allows for a quick and easy development and analysis of agent-based coordination mechanisms for the Grid
This project simulates a multi-agent system (swarm) behavior both graphically and not. The purpose of this project is to research the properties suggested in "stability analysis of swarms" V.Gazi & K.M.Passino. Using the vpython library for 3D modeling
The goals of RAFALE-SP is to create agent based mobility simulators. This toolkit is specialized to reproduce real mobility which take place on a real area like a town, a country and so on.
TrafSim is a scientific/research project that uses Agent-Based Modeling to simulate traffic. The aim is analyzing some emergent properties of interaction of these agents (cars/drivers) in a cross or high-way with U-turn structures.
Agent based model of organizations considering the interplay between the formal hierarchical structure and the process network emerging while the organization performs a task-set.
ABSim is an Agent-Object-Relationship (AOR) simulation system based on a Java program library. The development of ABSim has terminated. Its successor is <a href="http://oxygen.informatik.tu-cottbus.de/aor/?q=node/2">AOR-JSim </a>
This is a framework to develop Contexts and Agents and a Container to run them. The Container lets each Agent interact with the Context and other Agents. The agents are deployed in jar files and each one runs in an exclusive sandbox.
SeSAm (Shell for Simulated Agent Systems) provides a generic environment for modelling and experimenting with agent-based simulation with a special focus on the easy construction of complex models including dynamic interdependencies or emergent behaviour
Trading Agent Competition (TAC) is an international forum designed to promote and encourage high quality research into the trading agent problem.
The TAC SCM open-source software consists of a Java-based Game Server and and library for developing agents.
SimForge is a web-based Agent Based Model of an Open Source Ecosystem implemented in Python with Django. Developers act on randomly drawn preferences to create, collaborate, and use software.