Search Results for "multi-objective optimization"
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8 projects for "multi-objective optimization" with 2 filters applied:
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Full-stack observability with actually useful AI | Grafana CloudBuilt on open standards like Prometheus and OpenTelemetry, Grafana Cloud includes Kubernetes Monitoring, Application Observability, Incident Response, plus the AI-powered Grafana Assistant. Get started with our generous free tier today.
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MongoDB Atlas runs apps anywhereMongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
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Open Gauss
Project-scoped Lean workflow orchestrator from Math, Inc.
...The database organizes data using the relational model, storing structured information in tables composed of rows and columns while supporting standard SQL for querying and management. One of its defining strengths is its optimization for multi-core and distributed environments, allowing it to efficiently process high volumes of concurrent transactions with minimal latency. OpenGauss also incorporates AI-based optimization techniques, such as intelligent query planning, performance prediction, and automated tuning, which help reduce operational complexity and improve efficiency. -
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Agent Reinforcement Trainer
Train multi-step agents for real-world tasks using GRPO
Agent Reinforcement Trainer, or ART is an open-source reinforcement learning framework tailored to training large language model agents through experience, making them more reliable and performant on multi-turn, multi-step tasks. Instead of just manually crafting prompts or relying on supervised fine-tuning, ART uses techniques like Group Relative Policy Optimization (GRPO) to let agents learn from environmental feedback and reward signals. The framework is designed to integrate easily with Python applications, abstracting much of the RL infrastructure so developers can train agents without deep RL expertise or heavy infrastructure overhead. ... -
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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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CUDA Agent
Large-Scale Agentic RL for High-Performance CUDA Kernel Generation
CUDA Agent is a research-driven agentic reinforcement learning system designed to automatically generate and optimize high-performance CUDA kernels for GPU workloads. The project addresses the long-standing challenge that efficient CUDA programming typically requires deep hardware expertise by training an autonomous coding agent capable of iterative improvement through execution feedback. Its architecture combines large-scale data synthesis, a skill-augmented CUDA development environment,... -
$300 Free Credits to Build on Google CloudStart 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.
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Coze Loop
Next-generation AI Agent Optimization Platform
Coze Loop is a developer-oriented platform that provides full lifecycle management for AI agents, covering everything from prompt engineering to production monitoring. The project aims to simplify the increasingly complex workflow of building reliable AI agents by offering integrated tools for debugging, evaluation, observability, and optimization. Through its visual playground, developers can test prompts interactively and compare outputs across different language models. The platform also... -
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Agent Lightning
The absolute trainer to light up AI agents
Agent Lightning is an open-source framework developed by Microsoft to train and optimize AI agents using techniques like reinforcement learning (RL), supervised fine-tuning, and automatic prompt optimization, with minimal or zero changes to existing agent code. It’s designed to be compatible with a wide range of agent architectures and frameworks — from LangChain and OpenAI Agent SDKs to AutoGen and custom Python agents — making it broadly applicable across different agent tooling... -
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RecursiveMAS
Offical Implementation for "Recursive Multi-Agent Systems"
RecursiveMAS is an advanced multi-agent AI framework that introduces a recursive collaboration mechanism to improve reasoning and problem-solving across multiple agents. Instead of treating agents as independent units exchanging text outputs, it connects them through a shared latent computation loop, allowing internal “thought states” to be passed and refined iteratively. This recursive structure enables agents to build on each other’s intermediate reasoning, leading to deeper and more... -
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Swift Concurrency Agent Skill
Add expert Swift Concurrency guidance to your AI coding tool
Swift Concurrency Agent Skill is an open-source “agent skill” designed to give AI coding assistants deep expertise in Apple’s Swift Concurrency model, including async/await, structured concurrency, task groups, actors, and thread safety. It is formatted according to the Agent Skills specification so that tools like Claude Code, Cursor, Copilot, and other LLM-powered systems can load it and apply guidance when relevant. The skill codifies practical best practices for writing efficient, safe,...
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