Showing 4 open source projects for "decision analysis"

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    AI Berkshire

    AI Berkshire

    AI-era Berkshire: a value investing research framework

    ...It turns the investment methods of Warren Buffett, Charlie Munger, Duan Yongping, and Li Lu into structured research agents. The project is meant to improve research depth, decision discipline, and analytical consistency compared with asking a general AI model for a one-off stock opinion. It uses parallel agent analysis, adversarial viewpoints, financial rigor checks, and repeatable report formats to reduce shallow or overly balanced conclusions. The framework covers company research, earnings review, industry screening, portfolio thinking, management analysis, and investment checklists. ...
    Downloads: 1 This Week
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    TradingAgents

    TradingAgents

    Chinese Financial Trading Framework Based on Multi-Agent LLM

    TradingAgents-CN is a Chinese-enhanced, multi-agent LLM framework aimed at building financial analysis and trading-oriented workflows, with an emphasis on collaboration between specialized agents rather than a single monolithic prompt. It organizes market-related tasks into roles and stages so different agents can contribute research, reasoning, aggregation, and decision support in a structured pipeline. The project is oriented toward practical usage, including a stack that can be run in a modern development environment and commonly paired with containerized backends, configuration files, and service components. ...
    Downloads: 2 This Week
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  • 3
    OWL

    OWL

    Optimized Workforce Learning for General Multi-Agent Assistance

    OWL (Optimized Workforce Learning) is a sophisticated open-source framework built on the CAMEL-AI ecosystem for orchestrating teams of AI agents to collaboratively solve complex, real-world tasks with dynamic planning and automation capabilities. Unlike single-agent systems, it treats task completion as a collaborative workforce where agents take on specialized roles (planning, execution, analysis) and coordinate via a modular multi-agent architecture that supports flexible teamwork across domains. OWL delivers state-of-the-art performance on benchmarks like GAIA and emphasizes real-time decision-making, web automation, rich search integration, document parsing, and multi-tool workflows, making it suitable for tasks ranging from information retrieval to interactive automation.
    Downloads: 1 This Week
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  • 4
    Accord.NET Framework

    Accord.NET Framework

    Scientific computing, machine learning and computer vision for .NET

    The Accord.NET Framework provides machine learning, mathematics, statistics, computer vision, computer audition, and several scientific computing related methods and techniques to .NET. The project is compatible with the .NET Framework. NET Standard, .NET Core, and Mono.
    Downloads: 2 This Week
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