Skip to main content

A Python package for the rapid development and evaluation of human-agent teaming concepts.

Project description

The MATRX Software

Human-Agent Teaming Rapid Experimentation Software

The field of human-agent teaming (HAT) research aims to improve the collaboration between humans and intelligent agents. Small tasks are often designed to do research in agent development and perform evaluations with human experiments. Currently there is no dedicated library of such tasks. Current tasks are build and maintained independent of each other, making it difficult to benchmark research or explore research to different type of tasks.

To remedy the lack of a team task library for HAT research, we developed the Human-Agent Teaming Rapid Experimentation Software package, or MATRX for short. MATRX’s main purpose is to provide a suite of team tasks with one or multiple properties important to HAT research (e.g. varying team size, decision speed or inter-team dependencies). In addition to these premade tasks, MATRX facilitates the rapid development of new team tasks.

Also, MATRX supports HAT solutions to be implemented in the form of Team Design Patterns (TDP). This allows for the creation of a TDP library which structures HAT research by mapping task properties, solutions and obtained results in such a way that identifies research gaps. Perhaps more importantly, it allows for system designers to search for a concrete and evaluated solution to their issues related to HAT.

This all is made possible by MATRX.

Feel free to try some tasks or to browse our official webpage. This also includes a set of elaborate tutorials, documentation and contribution guide. .

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

matrx-2.3.1.tar.gz (6.8 MB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

matrx-2.3.1-py3-none-any.whl (7.4 MB view details)

Uploaded Python 3

File details

Details for the file matrx-2.3.1.tar.gz.

File metadata

  • Download URL: matrx-2.3.1.tar.gz
  • Upload date:
  • Size: 6.8 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.0 CPython/3.8.10

File hashes

Hashes for matrx-2.3.1.tar.gz
Algorithm Hash digest
SHA256 857a2ac814aa65ccbe27b8bd1eecc0d87327167c43fb60946049fdb61adeb8cf
MD5 7d1baaed23bd01f7cf6f5bcc395ecf4e
BLAKE2b-256 f163aebfeb1e0cab05ba7bdc2ee65063e54803c91339a9b2bc2ae9752084858a

See more details on using hashes here.

File details

Details for the file matrx-2.3.1-py3-none-any.whl.

File metadata

  • Download URL: matrx-2.3.1-py3-none-any.whl
  • Upload date:
  • Size: 7.4 MB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.0 CPython/3.8.10

File hashes

Hashes for matrx-2.3.1-py3-none-any.whl
Algorithm Hash digest
SHA256 1f86afe9ac10b9d142c2e12dbbb27980eeb071485704580171b0210a82827b95
MD5 85250d7d759c21e7ff750878756f435b
BLAKE2b-256 310db5d9ae47d179b316c299b596ef33d3711f7407b943ce2c6f137927b90cea

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page