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In this paper published on Nature, AI researchers used deep Q-network with very good adaptability and obtained performances comparable to those of a human games tester.

Bastards! And that was to be my next idea. Still no recurrency as I see it so far, so this is just some fancy way to do a markov model. Not sure if this is that particular paper or an earlier version but here it is for those interested: http://www.cs.toronto.edu/~vmnih/docs/dqn.pdf

Paper: https://arxiv.org/abs/1806.02404

Our work sheds light on many interesting directions of future exploration in the development of quantum-inspired algorithms for unsupervised machine learning, which are promisingly possible to realize on quantum devices.

Prediction-based method for encouraging reinforcement learning agents to explore their environments through curiosity (reward for unfamiliar states). Learns some games without any extrinsic reward!

Fun failure case: agent gets stuck in front of TV.

Not read this article but on a related note: Curiosity and various metrics for it have been explored for some time in robotics (outside of RL) as a framework for exploring (partially) unfamiliar environments. I came across some papers on this topic applied to UAVs when prep'ing for a PhD app. This one (http://www.cim.mcgill.ca/~yogesh/publications/crv2014.pdf) comes to mind - which used a topic modelling approach.

Researchers have used machine learning to predict the chaotic evolution of a model flame front.

A college course at University of Washington on "Calling Bullshit". We should invite them to give a lunch lecture at ESA... Our aim in this course is to teach you how to think critically about the data and models that constitute evidence in the social and natural sciences. While bullshit may reach its apogee in the political domain, this is not a course on political bullshit. Instead, we will focus on bullshit that comes clad in the trappings of scholarly discourse. Our learning objectives are straightforward. After taking the course, you should be able to: * Remain vigilant for bullshit contaminating your information diet. * Recognize said bullshit whenever and wherever you encounter it. * Figure out for yourself precisely why a particular bit of bullshit is bullshit. * Provide a statistician or fellow scientist with a technical explanation of why a claim is bullshit. * Provide your crystals-and-homeopathy aunt or casually racist uncle with an accessible and persuasive explanation of why a claim is bullshit. We will be astonished if these skills do not turn out to be among the most useful and most broadly applicable of those that you acquire during the course of your college education.

love it: "Politicians are unconstrained by facts. Science is conducted by press release. Higher education rewards bullshit over analytic thought. Startup culture elevates bullshit to high art. Advertisers wink conspiratorially and invite us to join them in seeing through all the bullshit - and take advantage of our lowered guard to bombard us with bullshit of the second order. The majority of administrative activity, whether in private business or the public sphere, seems to be little more than a sophisticated exercise in the combinatorial reassembly of bullshit. We're sick of it. It's time to do something, and as educators, one constructive thing we know how to do is to teach people. So, the aim of this course is to help students navigate the bullshit-rich modern environment by identifying bullshit, seeing through it, and combating it with effective analysis and argument."

"The Neuromorphic Computing Platform allows neuroscientists and engineers to perform experiments with configurable neuromorphic computing systems. The platform provides two complementary, large-scale neuromorphic systems built in custom hardware at locations in Heidelberg, Germany (the "BrainScaleS" system, also known as the "physical model" or PM system) and Manchester, United Kingdom (the "SpiNNaker" system, also known as the "many core" or MC system)."

Material point method is an efficient and promising method for simulating complex stuff. Not used much in Astro, a lot in gaming, cartoons etc.... Worth having a look in comparison with SPH in simulation (for example those connected to the HERAS mission)

Let's keep a eye on this... Animals use odor cues to navigate through their environments, helping them locate targets and assess danger. Much of how animal brains organize, read out, and respond to odor stimuli across spatial and temporal scales is not well understood. To tackle these questions, Odor2Action uses a highly interdisciplinary team science approach. Our work uses fruit fly, honeybee, and mouse models to determine how neural representations of odor are generated, reformatted, and translated to generate useful behaviors that guide how animals interact with their environment.

reminds me of the methan smelling source finding study we did ...