Mirek Olšák Charles University We introduce a theorem proving algorithm that uses practically no domain heuristics for guiding its connection-style proof search. Instead, it runs many Monte-Carlo simulations guided by reinforcement learning from previous proof attempts. We produce several versions of the prover, parameterized by different learning and guiding algorithms. The strongest version of the system is trained on a large corpus of mathematical problems and evaluated on previously unseen problems. The trained system solves within the same number of inferences over 40% more problems than a baseline prover, which is an unusually high improvement in this hard AI domain. To our knowledge this is the first time reinforcement learning has been convincingly applied to solving general mathematical problems on a large scale.

Multi-output Gaussian processes (MOGP) generalise the powerful Gaussian process (GP) predictive model to the vector-valued random field setup (Alvarez et al., 2012). It has been experimentally shown that by simultaneously exploiting correlations between multiple outputs and across the input space, it is possible to provide better predictions, particularly in scenarios with missing or noisy data (Bonilla et al., 2008; Dai et al., 2017). The main focus in the literature for MOGP has been on the definition of a suitable cross-covariance function between the multiple outputs that allows for the treatment of outputs as a single GP with a properly defined covariance function (Alvarez et al., 2012). The two classical alternatives to define such cross-covariance functions are the linear model of coregionalisation (LMC) (Journel and Huijbregts, 1978) and process convolutions (Higdon, 2002). In the former case, each output corresponds to a weighted sum of shared latent random functions.

This paper describes the deployment and implementation of a blockchain to improve the security, knowledge and intelligence during the inter-agent communication and collaboration processes in restrict domains of the Internet Infrastructure. It is a work that proposes the application of a blockchain, platform independent, on a particular model of agents, but that can be used in similar proposals, once the results on the specific model were satisfactory.

Watchlist (also hint list) is a mechanism that allows related proofs to guide a proof search for a new conjecture. This mechanism has been used with the Otter and Prover9 theorem provers, both for interactive formalizations and for human-assisted proving of open conjectures in small theories. In this work we explore the use of watchlists in large theories coming from first-order translations of large ITP libraries, aiming at improving hammer-style automation by smarter internal guidance of the ATP systems. In particular, we (i) design watchlist-based clause evaluation heuristics inside the E ATP system, and (ii) develop new proof guiding algorithms that load many previous proofs inside the ATP and focus the proof search using a dynamically updated notion of proof matching. The methods are evaluated on a large set of problems coming from the Mizar library, showing significant improvement of E's standard portfolio of strategies, and also of the previous best set of strategies invented for Mizar by evolutionary methods.

The technical skills of programmer John Carmack helped create the 3D world of Doom, the first-person shooter that took over the world 25 years ago. But it was level designers like John Romero and American McGee that made the game fun to play. Level designers that, today, might find their jobs threatened by the ever-growing capabilities of artificial intelligence. One of the many reasons Doom became so incredibly popular was that id Software made tools available that let anyone create their own levels for the game, resulting in thousands of free ways to add to its replay value. First-person 3D games and their level design have advanced by leaps and bounds since the original Doom's release, but the sheer volume of user-created content made it the ideal game for training an AI to create its own levels.

Researchers in France have built a teeny, tiny house. It's just a few micrometers wide, too small for even a mite to fit inside, and demonstrates that a focused ion beam and a small robot can create 3D microstructures with incredible accuracy and precision. "For the first time we were able to realize patterning and assembly with less than two nanometers of accuracy, which is a very important result for the robotics and optical community," Jean-Yves Rauch, a researcher on the project, said in a statement. The work was published recently in the Journal of Vacuum Science and Technology A. First, a thin sheet of silica was placed on the tip of an optical fiber and then an ion beam was used to cut out the shape of the house and its windows. To fold the walls up, the ion beam was used to just score the silica membrane, and once it was thin enough, it folded up 90 degrees all on its own.

One day last summer, Microsoft's director of artificial intelligence research, Eric Horvitz, activated the Autopilot function of his Tesla sedan. The car steered itself down a curving road near Microsoft's campus in Redmond, Washington, freeing his mind to better focus on a call with a nonprofit he had cofounded around the ethics and governance of AI. Then, he says, Tesla's algorithms let him down. "The car didn't center itself exactly right," Horvitz recalls. Both tires on the driver's side of the vehicle nicked a raised yellow curb marking the center line, and shredded.

If last week was the week of E3 rumors, this is the week of delays. Phoenix Point, Metro: Exodus, and Skull & Bones were all pushed back this week, meaning the first few months of 2019 are already looking busy. This is gaming news for May 14 to 18. Let's get the Call of Duty news out of the way first, if only because there's a lot of it. This week was the Black Ops IIII reveal event, and the biggest news? That's not entirely unexpected, given Activision did the same with Destiny 2 last year. I guess we should probably expect all major Activision games to be Battle.net

West explains that as robots, artificial intelligence, and automation make it possible to be more productive while working fewer hours, society must change its definition of work. Also in this episode, foreign policy expert Célia Belin unveils why she became a scholar and Susan Hennessey introduces Sourcelist, a database of experts in technology policy from diverse backgrounds. Can France be America's new bridge to Europe? The'Macron miracle' could transform France into a global powerhouse Additional support comes from Jessica Pavone, Eric Abalahin, Rebecca Viser, our intern Steven Lee, Camilo Ramirez, and David Nassar. Subscribe to Brookings podcasts here or on Apple Podcasts, send feedback email to BCP@Brookings.edu, and follow us and tweet us at @policypodcasts on Twitter.