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    Safety Gym on Ubuntu 26.04 with Maintenance Support by kCloudHubs

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    Deployed on AWS
    AWS Free Tier
    This product has charges associated with it for seller support. Safety Gym is an open-source toolkit developed by OpenAI for studying safety in reinforcement learning. It provides simulated environments where agents must complete tasks while avoiding risks like collisions or unsafe actions. It is mainly used by researchers to design and test algorithms that prioritize both performance and safety.

    Overview

    This is a repackaged open-source software product wherein additional charges apply for support. Safety Gym on Ubuntu 26.04 provides a research-oriented environment for studying safety in reinforcement learning. It enables researchers and developers to evaluate reinforcement learning agents in simulated scenarios where they must complete tasks while respecting safety constraints. This makes it useful for developing and testing algorithms that consider both performance and safe behavior.

    Safety Gym provides configurable environments containing obstacles, hazards, and task-specific constraints. These environments allow users to experiment with reinforcement learning policies, compare agent behavior, and analyze how effectively agents achieve objectives while minimizing unsafe actions. The platform is particularly useful for research in safe AI, robotics, autonomous systems, and reinforcement learning.

    Key Features

    • Environment for research in safe reinforcement learning.
    • Simulated tasks with safety constraints and hazards.
    • Support for evaluating agent performance and safety behavior.
    • Configurable environments for reinforcement learning experiments.
    • Useful for testing policies under safety-related constraints.
    • Suitable for AI, robotics, and autonomous systems research.
    • Designed for experimentation, benchmarking, and algorithm development.

    Safe Reinforcement Learning

    Safety Gym helps researchers study reinforcement learning approaches where agents must optimize task objectives while avoiding unsafe behavior. By incorporating safety constraints into simulated environments, users can investigate how different algorithms respond to risks and evaluate trade-offs between performance and safety.

    Research and Development

    The environment can be used for experimentation with reinforcement learning algorithms, policy evaluation, benchmarking, and safety-oriented AI research. It provides a controlled setting for testing agent behavior before applying concepts to more complex or real-world systems.

    Ubuntu 26.04 Deployment

    • Safety Gym environment configured on Ubuntu 26.04.
    • Ready-to-use platform for reinforcement learning research.
    • Suitable for development, testing, experimentation, and academic research.
    • Compatible with modern Python-based AI and machine learning workflows.
    • Suitable for AWS EC2 and cloud-based research environments.

    Use Cases

    • Safe reinforcement learning research.
    • AI agent safety evaluation.
    • Robotics and autonomous systems research.
    • Reinforcement learning benchmarking.
    • Simulation-based AI experimentation.
    • Policy testing and algorithm development.
    • Academic and experimental machine learning projects.

    Maintenance Support by kCloudHubs

    kCloudHubs provides maintenance support for the Safety Gym environment on Ubuntu 26.04. Support may include installation and configuration assistance, troubleshooting, environment maintenance, dependency guidance, updates, and operational assistance for supported research workloads.

    Keywords: Safety Gym, safe reinforcement learning, reinforcement learning, AI safety, machine learning, AI agents, robotics, autonomous systems, simulation, reinforcement learning research, AI research, Ubuntu 26.04, Python, kCloudHubs.

    Highlights

    • Focuses on safe reinforcement learning, not just performance.
    • Built on physics engines for realistic interactions.
    • Helps test how agents avoid risks while achieving goals.

    Details

    Delivery method

    Delivery option
    64-bit (x86) Amazon Machine Image (AMI)

    Latest version

    Operating system
    Ubuntu 26.04

    Deployed on AWS
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    Pricing

    Safety Gym on Ubuntu 26.04 with Maintenance Support by kCloudHubs

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    Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time.
    Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator  to estimate your infrastructure costs.
    If you are an AWS Free Tier customer with a free plan, you are eligible to subscribe to this offer. You can use free credits to cover the cost of eligible AWS infrastructure. See AWS Free Tier  for more details. If you created an AWS account before July 15th, 2025, and qualify for the Legacy AWS Free Tier, Amazon EC2 charges for Micro instances are free for up to 750 hours per month. See Legacy AWS Free Tier  for more details.

    Usage costs (21)

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    Dimension
    Cost/hour
    m4.large
    Recommended
    $0.10
    t2.micro
    $0.001
    t3.micro
    $0.10
    t3.large
    $0.10
    r3.large
    $0.10
    r4.large
    $0.10
    t2.large
    $0.10
    t3.medium
    $0.10
    t2.2xlarge
    $0.10
    t2.medium
    $0.10

    Vendor refund policy

    No Refund

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    Usage information

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    Delivery details

    64-bit (x86) Amazon Machine Image (AMI)

    Amazon Machine Image (AMI)

    An AMI is a virtual image that provides the information required to launch an instance. Amazon EC2 (Elastic Compute Cloud) instances are virtual servers on which you can run your applications and workloads, offering varying combinations of CPU, memory, storage, and networking resources. You can launch as many instances from as many different AMIs as you need.

    Version release notes

    Packaged with latest updates as of June 2026.

    Additional details

    Usage instructions

    Connect your instance via SSH, the username is ubuntu. More info on SSH: https://docs.aws.amazon.com/AWSEC2/latest/UserGuide/AccessingInstancesLinux.html  - Run the following commands: #sudo su #sudo apt update #cd /opt/safety #source venv/bin/activate #pip show safety-gymnasium

    Support

    Vendor support

    Feel free to reach out anytime. Our support team is available 24x7 for assistance mail: meha@kcloudhubs.com 

    AWS infrastructure support

    AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.

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