Robotics, Autonomous Intelligence and Learning Lab


The RAIL Lab, established in 2014, is dedicated to conducting cutting-edge research in the field of artificially intelligent systems. With a focus on both fundamental and applied research, our vision is to serve as a prominent centre of excellence and a hub for AI activities in Africa. We aim to make significant contributions to the field of AI while also applying our findings to benefit society at large.

Robotics, Autonomous Intelligence and Learning Lab

Latest Research


Transferable Dynamics Models for Efficient Object-Oriented Reinforcement Learning

The Reinforcement Learning (RL) framework offers a general paradigm for constructing autonomous agents that can make effective …

Counting Reward Automata: Sample Efficient Reinforcement Learning Through the Exploitation of Reward Function Structure

We present counting reward automata—a finite state machine variant capable of modelling any reward function expressible as a …

Towards Financially Inclusive Credit Products Through Financial Time Series Clustering

Financial inclusion ensures that individuals have access to financial products and services that meet their needs. As a key …

MiDaS: A Large-Scale Minecraft Dataset for Non-Natural Image Benchmarking

Reinforcement learning (RL) has recently made several significant advances using video games as a testbed. While many of these games …

Dynamics Generalisation in Reinforcement Learning via Adaptive Context-Aware Policies

While reinforcement learning has achieved remarkable successes in several domains, its real-world application is limited due to many …

Generalisable Agents for Neural Network Optimisation

Optimising deep neural networks is a challenging task due to complex training dynamics, high computational requirements, and long …