Ecology, Dynamical Systems and Inference via PMMH
Introduction In the 1920s, Lotka (1909) and Volterra (1926) developed a model of a very simple predator-prey ecosystem. Although simple, it turns out that the Canadian lynx and showshoe hare are well represented by such a model. Furthermore, the Hudson Bay Company kept records of how many pelts of each species were trapped for almost a century, giving a good proxy of the population of each species
1. Introduction QLearn: A Haskell library for iterative Q-learning. Reinforcement learning is a quickly growing field that's centered around teaching agents how to operate optimally in environments with states, actions and rewards associated with state and action pairs. QLearn is a library that allows you to easily implement Q-learning-based agents in Haskell. You can get it through Cabal: cabal i
In this post, we’re going to look at how to manipulate multivariate distributions in Haskell’s HLearn library. There are many ways to represent multivariate distributions, but we’ll use a technique called Markov networks. These networks have the algebraic structure called a monoid (and group and vector space), and training them is a homomorphism. Despite the scary names, these mathematical struc
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