Search Results for "agent based modelling"
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Showing 84 open source projects for "agent based modelling"
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PraisonAI
PraisonAI application combines AutoGen and CrewAI or similar framework
PraisonAI application combines AutoGen and CrewAI or similar frameworks into a low-code solution for building and managing multi-agent LLM systems, focusing on simplicity, customization, and efficient human-agent collaboration. Chat with your ENTIRE Codebase. Praison AI, leveraging both AutoGen and CrewAI or any other agent framework, represents a low-code, centralized framework designed to simplify the creation and orchestration of multi-agent systems for various LLM applications,... -
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CrewAI
Framework for orchestrating role-playing, autonomous AI agents
Framework for orchestrating role-playing, autonomous AI agents. By fostering collaborative intelligence, CrewAI empowers agents to work together seamlessly, tackling complex tasks. The power of AI collaboration has too much to offer. CrewAI is designed to enable AI agents to assume roles, share goals, and operate in a cohesive unit - much like a well-oiled crew. Whether you're building a smart assistant platform, an automated customer service ensemble, or a multi-agent research team, CrewAI... -
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LangGraph
Build resilient language agents as graphs
LangGraph is a library for building stateful, multi-actor applications with LLMs, used to create agent and multi-agent workflows. Compared to other LLM frameworks, it offers these core benefits: cycles, controllability, and persistence. LangGraph allows you to define flows that involve cycles, essential for most agentic architectures, differentiating it from DAG-based solutions. As a very low-level framework, it provides fine-grained control over both the flow and state of your application, crucial for creating reliable agents. ... -
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GPT Researcher
LLM based autonomous agent that does online comprehensive research
Say Hello to GPT Researcher, your AI agent for rapid insights and comprehensive research. GPT Researcher is the leading autonomous agent that takes care of everything from accurate source gathering to organization of research results. -
Go From AI Idea to AI App FastAccess Gemini 3 and 200+ models. Build chatbots, agents, or custom models with built-in monitoring and scaling.
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AutoGen
An Open-Source Programming Framework for Agentic AI
AutoGen is an open-source programming framework for building AI agents and facilitating cooperation among multiple agents to solve tasks. AutoGen aims to provide an easy-to-use and flexible framework for accelerating development and research on agentic AI, like PyTorch for Deep Learning. It offers features such as agents that can converse with other agents, LLM and tool use support, autonomous and human-in-the-loop workflows, and multi-agent conversation patterns. AutoGen provides... -
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smolagents
Agents write python code to call tools and orchestrate other agents
This library is the simplest framework out there to build powerful agents. We provide our definition in this page, where you’ll also find tips for when to use them or not (spoilers: you’ll often be better off without agents). smolagents is a lightweight framework for building AI agents using large language models (LLMs). It simplifies the development of AI-driven applications by providing tools to create, train, and deploy language model-based agents. -
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Codel
Fully autonomous AI Agent that can perform complicated tasks
Fully autonomous AI Agent that can perform complicated tasks and projects using terminal, browser, and editor. -
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AutoGroq
Revolutionizes the way users interact with Autogen
AutoGroq is a groundbreaking tool that revolutionizes the way users interact with Autogen™ and other AI assistants. By dynamically generating tailored teams of AI agents based on your project requirements, AutoGroq eliminates the need for manual configuration and allows you to tackle any question, problem, or project with ease and efficiency. AutoGroq was born out of the realization that the traditional approach to building AI agents was backwards. Instead of creating agents in anticipation... -
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EcoLab is a C++ based Agent Based Modelling system, with emphasis on high performance computing for scaling to large simulations.
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SalesGPT
Context-aware AI Sales Agent to automate sales outreach
This repo is an implementation of a context-aware AI Agent for Sales using LLMs and can work across voice, email and texting (SMS, WhatsApp, WeChat, Weibo, Telegram, etc.). SalesGPT is context-aware, which means it can understand what stage of a sales conversation it is in and act accordingly. Moreover, SalesGPT has access to tools, such as your own pre-defined product knowledge base, significantly reducing hallucinations. -
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Conscious Artificial Intelligence
It's possible for machines to become self-aware.
This project is a quest for conscious artificial intelligence. A number of prototypes will be developed as the project progresses. This project has 2 subprojects: Object Pascal based CAI NEURAL API - https://github.com/joaopauloschuler/neural-api Python based K-CAI NEURAL API - https://github.com/joaopauloschuler/k-neural-api A video from the first prototype has been made: http://www.youtube.com/watch?v=qH-IQgYy9zg Above video shows a popperian agent collecting mining ore from 3 mining sites and bringing to the base. ... -
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AgentVerse
Designed to facilitate the deployment of multiple LLM-based agents
AgentVerse is designed to facilitate the deployment of multiple LLM-based agents in various applications, which primarily provides two frameworks: task-solving and simulation. -
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Jason is a fully-fledged interpreter for an extended version of AgentSpeak, a BDI agent-oriented logic programming language, and is implemented in Java. Using JADE a multi-agent system can be distributed over a network effortlessly. This project was moved to https://jason-lang.github.io
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BDI4JADE is an agent platform based on the BDI architecture implemented in pure Java. Therefore, Java features can be exploited; and it facilitates the integration of existing technologies, what is essential in the context of enterprise applications.
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Simultra
Multiagent simulator of road traffic in Qt/C++ and OpenStreetMap.
...It combines microscopic and mesoscopic simulations into one multiagent hybrid simulator. The large-scale maps are modelled mesoscopically in real-time, and the complex traffic interactions benefit from detailed agent-based microscopic simulations. To resolve the concurrency issues within the maps representation and the meso-micro transitions, Simultra combines an event-based mesoscopic model of the maps with a more detailed physical engine. -
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PyGOAPng
Python Goal Oriented Action Planning (GOAP) library
A library for implementing GOAP in an AI agent. Based on pygoap v3 by Leif Theden et al. Updated code to work without having pygame installed, bug-fixed functions to make them implement the behaviors that were expected, and implemented desired behaviors so that the Pirate demo works properly for all known actions and goals. -
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WumpusWorld-CSharp
A Wumpus World in c# and prolog with a GUI
Wumpus World Game is based on knowledgebase agents and is described in the book , Artificial Intelligence : A Modern Approach (Russel - Norvig). This is an implementation of Wumpus World (a Knowledgebase agent game) using csharp alongside prolog with a GUI. C# has the main environment of the game and the GUI The GUI was created using WPF , Windows Presentation Foundation Prolog is used as the knowledgebase of the agent of Wumpus World In order for C# to communicate with Prolog a Csharp interface is used SWI-Prolog. ... -
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This project proposes a virtual laboratory for social scientists interested in the modelling, analysis and behavioral simulation of power relationships within organizations and more generally in systems of collective action. This software is grounded on the works lead by Sibertin-Blanc and Roggero on the formalization of the Sociology of Organised Action [Crozier and Freidberg]. Visit the homepage of the project on soclabproject.wordpress.com for tutorials, examples and further...
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Agent Factory is an open and extensible framework for developing and deploying agent systems that provides a FIPA-based distributed Run-Time Environment that supports the deployment of diverse agent types, ranging from bespoke, reactive to deliberative.
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SAJaS
Simple API for JADE-based Simulations
The Simple API for JADE-based Simulations (SAJaS) is a proposal to bridge the gap between MAS simulation and development. SAJaS enhances MABS frameworks with JADE-based features. While empowering MABS modellers with modelling concepts offered by JADE, SAJaS also promotes a quicker development of simulation models for JADE programmers. In fact, the same implementation can, with minor changes, be used as a large scale simulation or as a distributed JADE system. ... -
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MATSim is a framework for building multi-agent transport simulations. MATSim has moved to GitHub: https://github.com/matsim-org/matsim Source code and newer releases are now hosted at GitHub!
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dnrDALMAS
A general-level Prolog implementation of the DALMAS architecture.
DnrDALMAS is a Prolog module intended to be a general-level Prolog implementation of the abstract DALMAS (Deontic Action-Logic based Multi-Agent System) architecture. A DALMAS is regulated by a normative system based on an algebraic version of the theory of normative positions. For more information about dnrDALMAS, see the following technical report: Hjelmblom, M. (2008). Deontic action-logic multi-agent systems in Prolog. University of Gävle, Division of Computer Science; University of Gävle. http://urn.kb.se/resolve?... -
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GLORIA
a reasoning engine for agents and games
This project is about implementing a logic-programming based, reasoning engine for an agent. We started with an implementation of the iff-proof procedures, by Kowalski and Fung, as an any-time algorithm written in Prolog. -
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This project develops a Java API and tools to specify and execute organisations for multiagent systems based on Moise model. This model is built upon concepts like groups, roles, global goals and plans, and obligations.
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Argo for Jason
A Jason architecture for programming embedded robotic agents
In this architecture, Javino enables processing the data coming from sensors as perceptions in ARGO's agent reasoning cycle. Then, one can restrict the list of perceptions delivered by Javino based on filters designed by the agent's programmer. The main contribution of ARGO is to enable the use of perception filters for programming robotic agents. Moreover, ARGO allows an agent to decide when to start or to stop perceiving from its sensors, to fix the interval between each perception and to control these filtering behavior in runtime. ...
