5G Technology World

  • 5G Technology and Engineering
  • FAQs
  • Apps
  • Devices
  • IoT
  • RF
  • Radar
  • Wireless Design
  • Learn
    • 5G Videos
    • Ebooks
    • EE Training Days
    • FAQs
    • Learning Center
    • Tech Toolboxes
    • Webinars/Digital Events
  • Handbooks
    • 2024
    • 2023
    • 2022
    • 2021
  • Resources
    • Design Guide Library
    • EE World Digital Issues
    • Engineering Diversity & Inclusion
    • Engineering Training Days
    • LEAP Awards
  • Advertise
  • Subscribe

Artificially Intelligent Game Bots Pass the Turing Test on Turing’s Centenary

By Staff Author | September 26, 2012

An artificially intelligent virtual gamer created by computer scientists at The University of Texas at Austin has won the BotPrize by convincing a panel of judges that it was more human-like than half the humans it competed against.

The competition was sponsored by 2K Games and was set inside the virtual world of “Unreal Tournament 2004,” a first-person shooter video game. The winners were announced this month at the IEEE Conference on Computational Intelligence and Games.

“The idea is to evaluate how we can make game bots, which are nonplayer characters (NPCs) controlled by AI algorithms, appear as human as possible,” said Risto Miikkulainen, professor of computer science in the College of Natural Sciences. Miikkulainen created the bot, called the UT^2 game bot, with doctoral students Jacob Schrum and Igor Karpov.

The bots face off in a tournament against one another and about an equal number of humans, with each player trying to score points by eliminating its opponents. Each player also has a “judging gun” in addition to its usual complement of weapons. That gun is used to tag opponents as human or bot.

The bot that is scored as most human-like by the human judges is named the winner. UT^2, which won a warm-up competition last month, shared the honors with MirrorBot, which was programmed by Romanian computer scientist Mihai Polceanu.

The winning bots both achieved a humanness rating of 52 percent. Human players received an average humanness rating of only 40 percent. The two winning teams will split the $7,000 first prize.

The victory comes 100 years after the birth of mathematician and computer scientist Alan Turing, whose “Turing test” stands as one of the foundational definitions of what constitutes true machine intelligence. Turing argued that we will never be able to see inside a machine’s hypothetical consciousness, so the best measure of machine sentience is whether it can fool us into believing it is human.

“When this ‘Turing test for game bots’ competition was started, the goal was 50 percent humanness,” said Miikkulainen. “It took us five years to get there, but that level was finally reached last week, and it’s not a fluke.”

The complex gameplay and 3-D environments of “Unreal Tournament 2004” require that bots mimic humans in a number of ways, including moving around in 3-D space, engaging in chaotic combat against multiple opponents and reasoning about the best strategy at any given point in the game. Even displays of distinctively human irrational behavior can, in some cases, be emulated.

“People tend to tenaciously pursue specific opponents without regard for optimality,” said Schrum. “When humans have a grudge, they’ll chase after an enemy even when it’s not in their interests. We can mimic that behavior.”

In order to most convincingly mimic as much of the range of human behavior as possible, the team takes a two-pronged approach. Some behavior is modeled directly on previously observed human behavior, while the central battle behaviors are developed through a process called neuroevolution, which runs artificially intelligent neural networks through a survival-of-the-fittest gauntlet that is modeled on the biological process of evolution.

Networks that thrive in a given environment are kept, and the less fit are thrown away. The holes in the population are filled by copies of the fit ones and by their “offspring,” which are created by randomly modifying (mutating) the survivors. The simulation is run for as many generations as are necessary for networks to emerge that have evolved the desired behavior.

“In the case of the BotPrize,” said Schrum, “a great deal of the challenge is in defining what ‘human-like’ is, and then setting constraints upon the neural networks so that they evolve toward that behavior.

“If we just set the goal as eliminating one’s enemies, a bot will evolve toward having perfect aim, which is not very human-like. So we impose constraints on the bot’s aim, such that rapid movements and long distances decrease accuracy. By evolving for good performance under such behavioral constraints, the bot’s skill is optimized within human limitations, resulting in behavior that is good but still human-like.”

Miikkulainen said that methods developed for the BotPrize competition should eventually be useful not just in developing games that are more entertaining, but also in creating virtual training environments that are more realistic, and even in building robots that interact with humans in more pleasant and effective ways.

University of Texas at Austin

 

 

September 27, 2012


Filed Under: RF

 

Next Article

← Previous Article
Next Article →

Related Articles Read More >

Open RAN test service adds colocation capabilities
Switch operates DC to 20 GHz with 128 configurable connection states for asymmetric SerDes testing
Butler Matrix
Butler Matrix drives Wi-Fi and other phased-array antennas
Long-wire dipole antennas: still viable after more than a century

Featured Contributions

  • Overcome Open RAN test and certification challenges
  • Wireless engineers need AI to build networks
  • Why AI chips need PCIe 7.0 IP interconnects
  • circuit board timing How timing and synchronization improve 5G spectrum efficiency
  • Wi-Fi 7 and 5G for FWA need testing
More Featured Contributions

EE TECH TOOLBOX

“ee
Tech Toolbox: 5G Technology
This Tech Toolbox covers the basics of 5G technology plus a story about how engineers designed and built a prototype DSL router mostly from old cellphone parts. Download this first 5G/wired/wireless communications Tech Toolbox to learn more!

EE LEARNING CENTER

EE Learning Center
“5g
EXPAND YOUR KNOWLEDGE AND STAY CONNECTED
Get the latest info on technologies, tools and strategies for EE professionals.

Engineering Training Days

engineering
“bills
5G Technology World
  • Enews Signup
  • EE World Online
  • DesignFast
  • EDABoard Forums
  • Electro-Tech-Online Forums
  • Microcontroller Tips
  • Analogic Tips
  • Connector Tips
  • Engineer’s Garage
  • EV Engineering
  • Power Electronic Tips
  • Sensor Tips
  • Test and Measurement Tips
  • About Us
  • Contact Us
  • Advertise

Copyright © 2025 WTWH Media LLC. All Rights Reserved. The material on this site may not be reproduced, distributed, transmitted, cached or otherwise used, except with the prior written permission of WTWH Media
Privacy Policy

Search 5G Technology World