Search Results for "agents"

AI Researcher is an experimental open-source project that demonstrates how multiple AI agents can collaborate to conduct complex research tasks from start to finish with minimal human intervention. It orchestrates agents that can generate research questions, perform literature reviews, execute experiments, analyze results, and synthesize findings into structured outputs like reports or code. Each agent operates with clear roles — such as researcher, analyst, and summarizer — and they communicate through a task-management interface that ensures progress tracking and iterative refinement. ...

...The repository includes implementations, experimental data, and supporting research papers that accompany published studies. Notable works such as Weight Agnostic Neural Networks and Neuroevolution of Self-Interpretable Agents highlight the team’s exploration of how AI can learn more efficiently and transparently. Overall, this repository serves as an open research hub for sharing ideas and advancing the understanding of intelligent systems.

...This is an educational resource produced by OpenAI that makes it easier to learn about deep reinforcement learning (deep RL). For the unfamiliar, reinforcement learning (RL) is a machine learning approach for teaching agents how to solve tasks by trial and error. Deep RL refers to the combination of RL with deep learning. At OpenAI, we believe that deep learning generally, and deep reinforcement learning specifically, will play central roles in the development of powerful AI technology. To ensure that AI is safe, we have to come up with safety strategies and algorithms that are compatible with this paradigm. ...

Neural MMO is a massively multi-agent simulation environment developed by OpenAI for reinforcement learning research. It provides a persistent, procedurally generated world where thousands of agents can interact, compete, and cooperate in real time. The environment is inspired by Massively Multiplayer Online Role-Playing Games (MMORPGs), featuring resource gathering, combat mechanics, exploration, and survival challenges. Agents learn behaviors in a shared ecosystem that supports long-term training and emergent dynamics across large populations. ...

The main aim of this project is to design and develop a mechanism that can find all the “important” files inside a computer.

Ouroborus is an artificial life framework for mobile agents on a background of cellular automata. It can be used to teach and research topics such as population genetics, ecology and evolution. The demo includes a curses view and live Csound audio.

Springbots is a python application which takes a set of 2d physical structures built with nodes and movable springs and evolve them for specific tasks like walking, swimming and jumping using genetic algorithm.

Educational game framework supporting board games, strategy games, and other grid-based game boards. Currently uses Python/wxPython as the application language/library. C++ libs included to help create AI for the various games.

java-based complete Agent (Artificial Intelligence) Framework with all the features you might expect in an Agent Framework: Mobility, Autonomy, Distributed communication, Agents can be written in Java, Jython, or Beanshell.