Software agents are as much a creature of their environments as all creatures on earth are. We have been created by constant evolution brought about by surviving our environment, competing with other entities and succeeding to procreate new generations.

In order to create and evaluate software agents we need to create environments to test them in.

  • International Aerial Robotics Challenge – there have been six challenges set to date of increasing complexity, it’s absolutely amazing what the state of the art in robotics can achieve. The last solved challenge asked teams to build a completely autonomous drone which, without prior knowledge of the environment, flew into an unmanned nuclear facility, identified and located the control room, and sent pictures of the control instrumentation out to a second unmanned drone.  The next challenge is to enter an unknown territory and locate a USB key holding sensitive data:
  • The DARPA Grand Challenge – creating a driverless car which will traverse across unknown terrain, which has been successfully with a variety of different technologies, all of which worthy of further research.  The current challenge is set in an urban environment with other motor vehicles to be successfully negotiated.
  • The NASA Centennial Challenge – to find and retrieve samples of scientific interest in an unknown environment
  • The RoboCup challenge, which requires teams made up of autonomous robots to win a league against other robots.  The organizers are attempting to lead the way for a robotic team to beat the last winners of the World Cup by 2050.  They’ve got a long way to go:

Of more immediate interest are virtual challenges as these are more accessible for direct testing.

  • The Google AI Challenge – this is the third challenge that asks entrants to submit AI bots to compete with each other in virtual worlds, and the first I have entered.  The first year (Winter 2010) was inspired by Tron, competitors needed to take control of a light cycle and cause the other players to crash.  The second was based upon the game PlanetWars, developed by Galcon, competitors needed to take over planets given a number of spaceships.  This years is based upon ants, and competitors need to develop a hive mind which will grab the most food at the same time as destroying other ant hives, all of which takes up valuable resources.  Entrants build AI bots in pretty much any language they like, then submit them to the competitions central servers to be pitted against other agents.
  • Core Wars – A game that could only be thought up by a computer scientist.  Build a set of instructions which are let loose in a simulated computer memory stack, which then compete against other instruction sets to take over the whole memory.  Sounds very geeky but some ingenious entrants.
  • Mario AI Challenge – using an adapted version of Super Mario 3 for the Nintendo, build a software bot that can complete any level thrown at it.  As interesting as the entrants are, the game environment (Super Mario Infinite) is an excellent example of Procedurally Generated Content (more on this later).
  • The StarCraft AI Challenge – StarCraft is a real time strategy game that is celebrated as one of the most hectic and evenly balanced computer games of all time.  In Asia, specifically Korea, this is an international sport.  Most video games can be seen as challenges for AI, with a bot taking over the role of the human player.  All that is needed is an API so that the AI can understand what is happening in the game and relay instructions back to the game (although in some cases a lack of API can be overcome by screenscraping, and this in itself is an area of research as in some real world cases it may be easier to translate a video output than retrofit an API).  The interestig thing about StarCraft is the wealth of information that needs to be processed, the number of available strategies (pretty much infinite) and the real time nature of the game – this is far more complex than chess, although with the luxury of being able to ponder the next move for half an hour.  Here’s a video of a software AI playing (and beating) one of the top ranking players worldwide.
  • Many games open up API’s to allow AI builders to modify or completely recreate AI’s that play against the human player – one very sophisticated and challenging example is Civilization IV, and develop fans have taken to building an open source version called FreeCiv, which allows whole worlds to be built with independent AI’s for those with the time.

Pretty much every video game genre from poker through space and trading simulations, role playing games to first person shooters and platform games, can be used as a test bed for developing and evaluating AI techniques.

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