Reality is a Game

Game thinking from Adam Clare

Tag: Google+(Page 1 of 2)

Artificial Intelligence in Relation to Games

Artificial Intelligence (AI) has been said by many to bring us a utopia and, now more frequently, a dystopia. Regardless of where research into AI takes us we’ll be seeing the benefits in games in multiple ways. AIs are not new to games and have been used in games for a long time, what’s more is that a good way to test AIs is to use games.

In the 90s an IBM computer beat a world champion chess player and that was impressive at the time. A chess AI can be programmed relatively easy since there’s a set way to play (basically look at all possible moves of a set and pick the best one).

DeepMind

A Game like go is harder to program for and as a result was deemed to be a triumphant challenge for programmers to create a program that can beat a human (the quantity of what needs to be coded for is huge). Last month, Google’s DeepMind beat a top-tier European go player.

Instead of programming for every possible move like in Deep Blue, Google let their program learn on its own. “AlphaGo was not preprogrammed to play Go: rather, it learned using a general-purpose algorithm that allowed it to interpret the game’s patterns, in a similar way to how a DeepMind program learned to play 49 different arcade games.” This is striking because it’s a leap in how we make AIs that play games. We just toss the AI at the game and hope it learns what to do – just like we do with human players.

To hear more about the future of DeepMind watch this lecture by Demis Cassabas (founder of DeepMind) about the future and capabilities of artificial intelligence.

Challenges for DeepMind’s Artificial Intelligence

Does DeepMind seem too good to be true to you? It’s probably because the annoucnemtn around how it beat the go player is a big claim. Gary Marcus deconstructs the advancement and looks at the challenges AlphaGo (and AI in general) needs to still overcome.

But not so fast. If you read the fine print (or really just the abstract) of DeepMind’s Nature article, AlphaGo isn’t a pure neural net at all — it’s a hybrid, melding deep reinforcement learning with one of the foundational techniques of classical AI — tree-search, invented by Minsky’s colleague Claude Shannon a few years before neural networks were ever invented (albeit in more modern form), and part and parcel of much his students’ early work.

What’s more is that AI still hasn’t reached a level of knowledge and reasoning to deal with questions that require multiple contexts. Indeed, a recent test concluded that present AIs can’t beat an 8th grader.

The Allen Institute’s science test includes more than just trivia. It asks that machines understand basic ideas, serving up not only questions like “Which part of the eye does light hit first?” but more complex questions that revolve around concepts like evolutionary adaptation. “Some types of fish live most of their adult lives in salt water but lay their eggs in freshwater,” one question read. “The ability of these fish to survive in these different environments is an example of [what]?”

These were multiple-choice questions—and the machines still couldn’t pass, despite using state-of-the-art techniques, including deep neural nets. “Natural language processing, reasoning, picking up a science textbook and understanding—this presents a host of more difficult challenges,” Etzioni says. “To get these questions right requires a lot more reasoning.”

It’s only a matter of time until the AI teams get from the 8th grade to high school then to the university level.

How does this relate to games though? With smarter AI comes we will get better bots in games and we’ll see that making NPCs will get easier.

Developing a Unified AI Framework

This month Firas Safadi, Raphael Fonteneau, and Damien Ernst published a paper in the International Journal of Computer Games Technology about how we ought to think about AI in games. They argue that we need a unified framework for dealing with AI development and deployment in games.

Their paper, Artificial Intelligence in Video Games: Towards a Unified Framework, is worth a read and will undoubtedly shape how we think about AI in games for years to come. Think about the possibility that game engines will ship with a suite of default AI behaviours that can be easily modified by non-coders.

Here’s the abstract:

With modern video games frequently featuring sophisticated and realistic environments, the need for smart and comprehensive agents that understand the various aspects of complex environments is pressing. Since video game AI is often specifically designed for each game, video game AI tools currently focus on allowing video game developers to quickly and efficiently create specific AI. One issue with this approach is that it does not efficiently exploit the numerous similarities that exist between video games not only of the same genre, but of different genres too, resulting in a difficulty to handle the many aspects of a complex environment independently for each video game. Inspired by the human ability to detect analogies between games and apply similar behavior on a conceptual level, this paper suggests an approach based on the use of a unified conceptual framework to enable the development of conceptual AI which relies on conceptual views and actions to define basic yet reasonable and robust behavior. The approach is illustrated using two video games, Raven and StarCraft: Brood War.

GeoGuesser: Where Are You?

GeoGuesser is a great way to kill a couple minutes and see a little more of the world. The basic challenge is to figure out where in the world you are looking at. The site uses Google Maps to create this nice short game.

Sometimes you get randomly placed in a easy to figure out area and other times it’s as if you’ve been dropped in the middle of the desert. I found just looking at the architecture was enough of a clue, sometimes it took a guess of geology.

I averaged around 12000 – how about you?

Cheap, Quick, Simple Design in Unity and Google Warehouse

Unity 3D is a great game making engine that allows indie developers and larger companies focus on game design rather than building all the components a game needs to run. This is great, but there is still the issue of creating art for the game and for people like me that is always a problem.

Jamie Fristrom who is currently running a Kickstarter campaign for his game Energy hook explains how he was able to make a playable prototype that look alright using just Unity and Google Warehouse SketchUp models. The article at Gamasutra is worth a read as it goes into some great detail.

from kickstarter

Be warned though that it’s not just drag-and-drop from SketchUp into Unity as the models need some touching up to be able to run smoothly in Unity. Knowledge of SketchUp and Unity are obviously required before trying this all out. Plus, not all textures translate well into the game either.

So why even bother with this process? Fristrom outlines why you should care:

So this is a viable method of level construction for a variety of uses:

  • if you’re a hobbyist game developer

  • if you’re looking for placeholder assets to prototype with

  • if you’re looking for assets that will never be too close to the in-game camera (buildings in the distance; or a racing game where the off-track assets are whipping by at 100 mph)

  • if your game has a highly stylized non-photorealistic look

Doing this is unfortunately not appropriate for mobile development – even with Unity Pro, the performance of these assets are simply not good enough for mobile.

There are other ways to build an environment that may interest you too. Obviously, you can just use stock items and geometric shapes for testing the core of the game but often more is needed.

In the past I have used the Unity Asset Store and from some of the sites I’ve listed here to quickly create environments for cheap.

Unity’s history

If you’re like me you’ve wondered how Unity got so big so quickly and is so good at what it does. At Slashdot, they have a great article on the history and the creation of Unity 3D. It’s really neat to read about the design approach behind the software insofar that they were inspired by FinalCut Pro and how it opened up filmmaking to smaller teams.

Despite the big names using Unity3D, it’s the smaller developers that make Helgason especially proud. “Big companies could always make games, they would figure it out and buy technology or build it themselves,” he said, adding: “Where we really made a dent is making it so that these masses of people can not just build games but can build games using the same tools as the big guys.”

Leaders of Hyperreal Civilizations

Hyperreality is the inability to decipher which is real and fake in the real world. The concept comes from Jean Baudrillard and he sees consumerism hampering our ability as a culture to see the real. I accidentally found one the best examples of hyperreality when I Googled the other day for Mansa Musa.

For some context, when you search a famous person on Google the site will pull in an image of that person like so:
Ada Lovelace

Pretty nice feature right? Look at the image below of the search results for Mansa Musa:
Mansa Musa

You see that? Where Google usually puts an image of the person in question they have parsed the web and found that the best image to use is from the game Civilization IV!

I wondered if the other leaders from Civ IV and the newer Civ V (leaders) suffered from the same fate, and below are other leaders that get the hyperreal treatment:

Pachacuti (Incan):
Screen Shot 2013-01-12 at 12.17.24 PM

Huayna Capac (also Incan):
huayna capac

Gilgamesh:
Gilgamesh

Hammurabi (Babylon) gets a Civ 4 screenshot only in the thumbnail of his pictures:
Hammurabi

All the other leaders are too popular or too well documented to have Google deem a screenshot from a video game is the best image. If I’ve missed any leaders please let me know!

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