This is the Windows app named Agent Behavior Monitoring whose latest release can be downloaded as v1.0.2sourcecode.tar.gz. It can be run online in the free hosting provider OnWorks for workstations.
Download and run online this app named Agent Behavior Monitoring with OnWorks for free.
Follow these instructions in order to run this app:
- 1. Downloaded this application in your PC.
- 2. Enter in our file manager https://www.onworks.net/myfiles.php?username=XXXXX with the username that you want.
- 3. Upload this application in such filemanager.
- 4. Start any OS OnWorks online emulator from this website, but better Windows online emulator.
- 5. From the OnWorks Windows OS you have just started, goto our file manager https://www.onworks.net/myfiles.php?username=XXXXX with the username that you want.
- 6. Download the application and install it.
- 7. Download Wine from your Linux distributions software repositories. Once installed, you can then double-click the app to run them with Wine. You can also try PlayOnLinux, a fancy interface over Wine that will help you install popular Windows programs and games.
Wine is a way to run Windows software on Linux, but with no Windows required. Wine is an open-source Windows compatibility layer that can run Windows programs directly on any Linux desktop. Essentially, Wine is trying to re-implement enough of Windows from scratch so that it can run all those Windows applications without actually needing Windows.
SCREENSHOTS
Ad
Agent Behavior Monitoring
DESCRIPTION
Agent Behavior Monitoring is an open-source framework designed to monitor, evaluate, and improve the behavior of AI agents operating in real or simulated environments. The system focuses on agent behavior monitoring by collecting interaction data and analyzing how agents perform across different scenarios and tasks. Developers can use the framework to observe agent actions in both online production environments and offline evaluation settings, making it useful for debugging and performance analysis. Judgeval transforms agent interaction trajectories into structured evaluation datasets that can be used for reinforcement learning, supervised fine-tuning, or other forms of post-training improvement. The framework includes tools that analyze agent behavior patterns and group interaction trajectories by behavior type or topic, allowing researchers to detect weaknesses or unexpected behaviors.
Features
- Agent behavior monitoring across online and offline environments
- Trajectory analysis that groups agent actions by behavior patterns
- Evaluation datasets derived from real agent interaction logs
- Integration with reinforcement learning and post-training pipelines
- Custom scoring and evaluation modules for agent performance testing
- Error analysis tools for diagnosing agent reasoning failures
Programming Language
Python
Categories
This is an application that can also be fetched from https://sourceforge.net/projects/abm.mirror/. It has been hosted in OnWorks in order to be run online in an easiest way from one of our free Operative Systems.
