In the previous blog post we discussed the gorey details of generalised policy learning - the first task of CRL. We went into some very detailed mathematical description of dynamic...
In the previous blog post we developed some ideas and theory needed to discuss a causal approach to reinforcement learning. We formalised notions of multi-armed bandits (MABs), Markov Decision Processes...
In the previous blog post we discussed and motivated the need for a causal approach to reinforcement learning. We argued that reinforcement learning naturally falls on the interventional rung of...
As part of any honours degree at the University of Cape Town, one is obliged to write a thesis droning on about some topic. Luckily for me, applied mathematics can...
In our last discussion we discussed the so-called ‘rung two’ of the ladder of causation, discussing interventions and randomisation in control trials. This is an incredibly important field in the...
Last time we discussed how we can learn causal structure from data and thought about how this relates to machine learning. Specifically, we noticed that having more data in a...
Last time we briefly discussed the theory needed to start thinking about how we can learn, in the statistical sense, causal information from ‘dumb’ data. Some key points were that...
In the last episode we developed the first tools we need to develop the theory needed to formalise interventions and counterfactual reasoning. In this article we’ll discuss how we can...
Last time we discussed and motivated the need for a modern theory of causal inference. We developed some of the basic principles necessary to develop this theory, but we have...
