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.
Latest Research
LLMatic: Neural Architecture Search via Large Language Models and Quality Diversity Optimization
Large language models (LLMs) have emerged as powerful tools capable of accomplishing a broad spectrum of tasks. Their abilities span …
Skill Machines: Temporal Logic Skill Composition in Reinforcement Learning
It is desirable for an agent to be able to solve a rich variety of problems that can be specified through language in the same …
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 …