"games" entries

Four short links: 10 February 2016

Four short links: 10 February 2016

Bitcoin Textbook, Brain Books, Post-Quantum Crypto, and Amazon's Game Engine

  1. Princeton Bitcoin Book (PDF) — The Coursera course accompanying this book had 30,000 students in its first version, and it was a success based on engagement and end-of-course feedback. Large introduction to Bitcoin from Princeton. (via Cory Doctorow)
  2. A Quartet of Complementary Brain Books (Vaughan Bell) — The books have been chosen to complement each other and the idea is that if you read all four, you should have a solid grounding in modern cognitive neuroscience and beyond.
  3. NIST Report on Post-Quantum Cryptography (PDF) — in case you missed it, “post-quantum crypto” is “existing crypto relies on how hard it is to find the prime factors of large numbers, of which we suspect quantum computers may make a mockery. Wut to do?” The goal of post-quantum cryptography (also called quantum-resistant cryptography) is to develop cryptographic systems that are secure against both quantum and classical computers, and can interoperate with existing communications protocols and networks.
  4. Amazon Lumberyarda free, cross-platform, 3D game engine for you to create the highest-quality games, connect your games to the vast compute and storage of the AWS Cloud, and engage fans on Twitch. From Amazon.
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Four short links: 9 February 2016

Four short links: 9 February 2016

Collaborative Mario Agents, ElasticSearch at Scale, Anomaly Detection, Robotics Experiment

  1. Social Intelligence in Mario Bros (YouTube) — collaborative agents built by cognitive AI researchers … they have drives, communicate, learn from each other, and solve problems. Oh, and the agents are Mario, Luigi, Yoshi, and Toad within a Super Mario Brothers clone. No code or papers about it on the research group’s website yet, just a YouTube video and a press release on the university’s website, so appropriately adjust your priors for imminent world destruction at the hands of a rampaging super-AI. (via gizmag)
  2. How we Monitor and Run ElasticSearch at Scale (SignalFx) — sweet detail on metrics, dashboards, and alerting.
  3. Simple Anomaly Detection for Weekly PatternsRule-based heuristics do not scale and do not adapt easily, especially if we have thousands of alarms to set up. Some statistical approach is needed that is generic enough to handle many different metric behaviours.
  4. How to Design a Robotics Experiment (Robohub) — although there are many good experimental scientists in the robotic community, there has not been uniformly good experimental work and reporting within the community as a whole. This has advice such as “the five components of a well-designed experiment.”
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Four short links: 28 January 2016

Four short links: 28 January 2016

Augmented Intelligence, Social Network Limits, Microsoft Research, and Google's Go

  1. Chimera (Paper a Day) — the authors summarise six main lessons learned while building Chimera: (1) Things break down at large scale; (2) Both learning and hand-crafted rules are critical; (3) Crowdsourcing is critical, but must be closely monitored; (4) Crowdsourcing must be coupled with in-house analysts and developers; (5) Outsourcing does not work at a very large scale; (6) Hybrid human-machine systems are here to stay.
  2. Do Online Social Media Remove Constraints That Limit the Size of Offline Social Networks? (Royal Society) — paper by Robin Dunbar. Answer: The data show that the size and range of online egocentric social networks, indexed as the number of Facebook friends, is similar to that of offline face-to-face networks.
  3. Microsoft Embedding ResearchTo break down the walls between its research group and the rest of the company, Microsoft reassigned about half of its more than 1,000 research staff in September 2014 to a new group called MSR NExT. Its focus is on projects with greater impact to the company rather than pure research. Meanwhile, the other half of Microsoft Research is getting pushed to find more significant ways it can contribute to the company’s products. The challenge is how to avoid short-term thinking from your research team. For instance, Facebook assigns some staff to focus on long-term research, and Google’s DeepMind group in London conducts pure AI research without immediate commercial considerations.
  4. Google’s Go-Playing AIThe key to AlphaGo is reducing the enormous search space to something more manageable. To do this, it combines a state-of-the-art tree search with two deep neural networks, each of which contains many layers with millions of neuron-like connections. One neural network, the “policy network,” predicts the next move, and is used to narrow the search to consider only the moves most likely to lead to a win. The other neural network, the “value network,” is then used to reduce the depth of the search tree — estimating the winner in each position in place of searching all the way to the end of the game.
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Four short links: 30 November 2015

Four short links: 30 November 2015

Chinese Manufacturing, Visual Question Answering, Editing Animal Genes, and AIs for RTS Games

  1. Behind the Hoverboard Craze (BoingBoing) — Bernstein is interested in this phenomenon as “memeufacturing” — a couple of social-media stars (or garden-variety celebs) post viral videos of themselves using an obscure gadget, and halfway around the world, factories shut down their e-cig lines and convert them, almost overnight, to hoverboard manufacturing lines. Bernstein cites a source who says that there are 1,000 hoverboard factories in South China.
  2. neural-vqaVIS+LSTM model for Visual Question Answering. Scroll to the end and see the questions it’s answering about photos.
  3. Open Season in Editing Genes of Animals (NY Times) — “We’re going to see a stream of edited animals coming through because it’s so easy,” said Bruce Whitelaw, a professor of animal biotechnology at the Roslin Institute at the University of Edinburgh. “It’s going to change the societal question from, ‘If we could do it, would we want it?’ to, ‘Next year we will have it; will we allow it?’”
  4. RTS AI (PDF) — standard techniques used for playing classic board games, such as game tree search, cannot be directly applied to solve RTS games without the definition of some level of abstraction, or some other simplification. Interestingly enough, humans seem to be able to deal with the complexity of RTS games, and are still vastly superior to computers in these types of games. Talks about the challenges in writing AIs for Real-Time Strategy games.
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Four short links: 20 November 2015

Four short links: 20 November 2015

Table Mining, Visual Microphones, Platformed Government, and NP-Hard Video Games

  1. DeepDive — Stanford project to create structured data (SQL tables) from unstructured information (text documents) and integrate such data with an existing structured database. DeepDive is used to extract sophisticated relationships between entities and make inferences about facts involving those entities. Code is open source (Apache v2 license). (via Infoworld)
  2. Visual Microphone (MIT) — turn everyday objects — a glass of water, a potted plant, a box of tissues, or a bag of chips — into visual microphones using high-speed photography to detect the small vibrations caused by sound. (via Infoworld)
  3. 10 Rules for Distributed/Networked/Platformed Government (Richard Pope) — Be as vigilant against creating concentrations of power as you are in creating efficiency or bad user experiences. (via Paul Downey)
  4. Classic Nintendo Games are (Computationally) HardWe prove NP-hardness results for five of Nintendo’s largest video game franchises: Mario, Donkey Kong, Legend of Zelda, Metroid, and Pokemon.
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Parallax scrolling for iOS with Swift and Sprite Kit

Learn how to add this popular visual effect to your iOS project.

Up until the mid 1990s, the pinnacle of video game graphics was parallax scrolling: the use of multiple scrolling backgrounds, which created a sense of depth and perspective in the game. When you’re being a 2D game in Sprite Kit, you can create this effect by creating multiple sprites, and managing their position over time.

In this example, we’re creating a scene where there are four components, listed in order of proximity:

  • A dirt path
  • Some nearby hills
  • Some further distant hills
  • The sky

You can see the final scene below:

Read more…

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Four short links: 7 July 2015

Four short links: 7 July 2015

SCIP Berkeley Style, Regular Failures, Web Material Design, and Javascript Breakouts

  1. CS 61AS — Berkeley self-directed Structure and Interpretation of Computer Programs course.
  2. Harbingers of Failure (PDF) — We show that some customers, whom we call ‘Harbingers’ of failure, systematically purchase new products that flop. Their early adoption of a new product is a strong signal that a product will fail – the more they buy, the less likely the product will succeed. Firms can identify these customers either through past purchases of new products that failed, or through past purchases of existing products that few other customers purchase.
  3. Google Material Design LiteA library of Material Design components in CSS, JS, and HTML.
  4. Breakoutsvarious implementations of the classic game Breakout in numerous different [Javascript] engines.
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Four short links: 2 July 2015

Four short links: 2 July 2015

Mathematical Thinking, Turing on Imitation Game, Retro Gaming in Javascript, and Effective Retros

  1. How Not to be Wrong: The Power of Mathematical Thinking (Amazon) — Ellenberg chases mathematical threads through a vast range of time and space, from the everyday to the cosmic, encountering, among other things, baseball, Reaganomics, daring lottery schemes, Voltaire, the replicability crisis in psychology, Italian Renaissance painting, artificial languages, the development of non-Euclidean geometry, the coming obesity apocalypse, Antonin Scalia’s views on crime and punishment, the psychology of slime molds, what Facebook can and can’t figure out about you, and the existence of God. (via Pam Fox)
  2. What Turing Himself Said About the Imitation Game (IEEE) — fascinating history. The second myth is that Turing predicted a machine would pass his test around the beginning of this century. What he actually said on the radio in 1952 was that it would be “at least 100 years” before a machine would stand any chance with (as Newman put it) “no questions barred.”
  3. Impossible Mission in Javascript — an homage to the original, and beautiful to see. I appear to have lost all my skills in playing it in the intervening 32 years.
  4. Running Effective RetrospectivesEach change to the team’s workflow is treated as a scientific experiment, whereby a hypothesis is formed, data collected, and expectations compared with actual results.
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Four short links: 25 June 2015

Four short links: 25 June 2015

Enchanted Objects, SE Blogs, AI Plays Mario, and Google's Future of Work

  1. 16 Everyday Objects Enchanted by Technology (Business Insider) — I want a Skype cabinet between our offices at work.
  2. Software Engineering Blogs — ALL the blogs!
  3. MarI/O (YouTube) — clear explanation of how an evolutionary algorithm figures out how to play Mario.
  4. Google’s Monastic Vision for the Future of Work (New Yorker) — But it turns out that future-proofed life looks a lot like the vacuum-packed present. […] Inside, it is about turning Google into not only a lifestyle but a fully realized life. The return of the Company Town.
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Four short links: 2 June 2015

Four short links: 2 June 2015

Toyota Code, Sapir-Wharf-Emoji, Crowdsourcing Formal Proof, and Safety-Critical Code

  1. Toyota’s Spaghetti CodeToyota had more than 10,000 global variables. And he was critical of Toyota watchdog supervisor — software to detect the death of a task — design. He testified that Toyota’s watchdog supervisor ‘is incapable of ever detecting the death of a major task. That’s its whole job. It doesn’t do it. It’s not designed to do it.’ (via @qrush)
  2. Google’s Design Icons (Kevin Marks) — Google’s design icons distinguish eight kinds of airline seats but has none for trains or buses.
  3. Verigames — DARPA-funded game to crowdsource elements of formal proofs. (via Network World)
  4. 10 Rules for Writing Safety-Critical Code — which I can loosely summarize as “simple = safer, use the built-in checks, don’t play with fire.”
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