Showing 1 open source project for "agent based"

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  • Paessler: Easy to Use With Enterprise Power. Free Trial Icon
    Paessler: Easy to Use With Enterprise Power. Free Trial

    A low-code dashboard makes monitoring intuitive for any admin, while scripting and custom sensors give experts full control.

    You shouldn't have to choose between a monitoring tool that's easy to use and one that's powerful enough for a complex environment. PRTG's low-code interface lets any admin build dashboards, set alerts and monitor devices without scripting, while custom sensors and full API access are there when your team needs deeper control. One platform, no compromise. Download a free 30-day trial now.
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  • Build Securely on AWS with Proven Frameworks Icon
    Build Securely on AWS with Proven Frameworks

    Lay a foundation for success with Tested Reference Architectures developed by Fortinet’s experts. Learn more in this white paper.

    Moving to the cloud brings new challenges. How can you manage a larger attack surface while ensuring great network performance? Turn to Fortinet’s Tested Reference Architectures, blueprints for designing and securing cloud environments built by cybersecurity experts. Learn more and explore use cases in this white paper.
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    ICCV2019-Learning to Paint

    ICCV2019-Learning to Paint

    Learning to Paint With Model-based Deep Reinforcement Learning

    Learning to Paint is an open-source PyTorch implementation of a deep reinforcement learning system that teaches artificial agents to recreate images through sequential brushstrokes. Based on research presented at ICCV 2019, it combines a learned neural renderer with model-based reinforcement learning. The agent determines stroke positions, shapes, and colors while planning how to approximate a target image. It can reproduce complex visual textures using hundreds of strokes. Training does not require examples of human painting movements or recorded brushstroke sequences. ...
    Downloads: 0 This Week
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