Ant_racer is a virtual multi-agent pursuit-evasion platform that provides a game environment for studying multi-agent reinforcement learning. Built on OpenAI Gym and Mujoco, it allows users to simulate interactions between multiple autonomous agents in pursuit and evasion tasks. The platform supports implementation and testing of reinforcement learning algorithms such as DDPG in a physically realistic environment. It is useful for researchers and developers interested in AI multi-agent behaviors in dynamic scenarios.

JaCaMo provides a unified environment for designing and running multi-agent systems (MAS) by integrating three core components: the Jason agent programming language for BDI-based agents, CArtAgO for artifact-based environmental modeling, and Moise for specifying organizational structures and roles. Developers can write agent plans, define artifacts with operations, and organize groups of agents under normative frameworks. The platform includes tooling for simulation, debugging, and visualization of MAS interactions. With support for distributed execution, artifact repositories, and flexible messaging, JaCaMo enables rapid prototyping and research in areas like swarm intelligence, collaborative robotics, and distributed decision-making. Its modular design ensures scalability and extensibility across academic and industrial projects.

jason-RL adds a reinforcement learning layer to the Jason multi-agent framework, allowing AgentSpeak BDI agents to learn action-selection policies via reward feedback. It implements Q-learning and SARSA algorithms, supports configuration of learning parameters (learning rate, discount factor, exploration strategy), and logs training metrics. By defining reward functions in agent plans and running simulations, developers can observe agents improve decision making over time, adapting to changing environments without manual policy coding.

Label Studio is a robust open-source data labeling tool designed to handle various data types such as text, images, audio, and video. It enables data scientists and machine learning engineers to create high-quality training data. The platform offers interactive labeling, model evaluation, and the integration of popular ML models for pre-labeling tasks. Label Studio supports multi-user collaboration and provides both community and enterprise versions to suit different needs.

Neon AI revolutionizes the way businesses interact with their customers by offering advanced tools to create conversational AI applications. These applications understand user queries, provide personalized responses, and enhance overall user experience. With a focus on scalability and customization, Neon AI provides tailored solutions to meet the specific needs of diverse industries, including small businesses, large enterprises, academic institutions, and nonprofits. Its open-source platform ensures accessibility and continuous innovation.

OpenKoda is an AI-powered, open-source platform aimed at accelerating the application development process. It provides a plethora of pre-built application templates and customizable solutions to meet specific business needs. By leveraging modern technologies and open-source principles, OpenKoda aims to reduce the time and effort required for application development while maintaining high-quality standards.