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reinforcement learning

Exact reproducibility of stochastic simulations for parallel and serial algorithms simultaneously Random Stream Chunking

msuzen

Preamble  Figure: Visual description of random stream chunking, M.Suzen (2017) The advent of using computational sciences approaches, i.e., data science and machine learning, in the industry becomes more common practice in almost all organisations due to the democratisation of data science tools...

python machine learning numpy distributed computing parallel programming monte carlo stochastic simulations reinforcement learning random numbers

Misconceptions on non-temporal learning: When do machine learning models qualify as prediction systems?

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Preamble    Babylonian Tablet for square root of 2. (Wikipedia)Prediction implies a mechanics, as in knowing a form of a trajectory over time.  Strictly speaking a predictive system implies knowing a solution to the path, set of variable depending on time, time evolution of the system under...

machine learning causality applied mathematics deep learning supervised learning dynamical systems reinforcement learning interpretable machine learning representation learning

Building robust AI systems: Is an artificial intelligent agent just a probabilistic boolean function?

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Preamble    George Boole (Wikipedia)Agent, AI agent or an intelligent agent is used often to describe algorithms or AI systems that are released by research teams recently. However, the definition of an intelligent agent (IA) is a bit opaque. Naïvely thinking, it is nothing more than a decision...

functional programming causality deep learning reinforcement learning interpretable machine learning connectionist learning robustness bayesian statistics.