October 28–31, 2019

EasyAgents: Reinforcement Learning for people who want to solve real-world problems

Christian Hidber (bSquare) Moderated by: Oliver Zeigermann, Christian Hidber


In this poster session we will both introduce the idea of Reinforcement Learning as well illustrate how Easyagents helps you with getting started with it. EasyAgents wraps reinforcement learning libraries like tf-agents or OpenAI baselines. The API is inspired by Keras and Scikit-learn and aims to get people started with reinforcement learning quickly, without having to learn any details of algorithms. We will show the diagrams and videos that are generated as default. You will also see the complete code for a small example.

Easyagents is free open source can be found here: https://github.com/christianhidber/easyagents

Photo of Christian Hidber

Christian Hidber


Christian Hidber is a software engineer at bSquare, where he applies machine learning to industrial hydraulics simulation, part of a product with 7,000 installations in 42 countries. He holds a PhD in computer algebra from ETH Zurich, which he followed with a postdoc at UC Berkeley, where he researched online data mining algorithms.

  • O'Reilly
  • TensorFlow
  • Google Cloud
  • IBM
  • Databricks
  • Tensor Networks
  • VMware
  • Amazon Web Services
  • One Convergence
  • Quantiphi
  • Lambda Labs
  • Tech Mahindra
  • cnvrg.io
  • Determined AI
  • Inferencery
  • Manceps, Inc.
  • PerceptiLabs
  • Valohai

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