---
title: "Encoding and Combining Knowledge to Speed up Reinforcement Learning"
authors:
  - "Tim Brys"
doi: ""
url: "https://ijcai.org/proceedings/2015/621"
pdf: "https://ijcai.org/proceedings/2015/0621.pdf"
venue: "Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence"
year: 2015
pages: "4347-4347"
track: "Doctoral Consortium"
keywords:
---

# Encoding and Combining Knowledge to Speed up Reinforcement Learning

Tim Brys

*Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence*, pages 4347-4347.

## Abstract

Reinforcement learning algorithms typically require too many `trial-and-error' experiences before reaching a desirable behaviour. A considerable amount of ongoing research is focused on speeding up this learning process by using external knowledge. We contribute in several ways, proposing novel approaches to transfer learning and learning from demonstration, as well as an ensemble approach to combine knowledge from various sources.