Download MI competition 2003

MI competition 2008
Summary of Entries
Entry 1: Nottingham Trent University, Hemin Omer Latif ([email protected])
Name of System: Teleoperated and Automated Person Following for Mobile Robots
Description of system: GazeBot is a mobile robot that demonstrates a combination of teleoperated and
automated capabilities. An automated person following capability enables GazeBot to follow a moving person and keep a
desired distance using one camera and based on vision cues only. While a specially developed interface called TeleGaze
enables teleoperation of the GazeBot whenever is required. The TeleGaze interface enables a human operator to select the
person of interest from the scene that is being monitored. Once a person being selected, the automated person following
starts following and searching for the person of interest if it has lost it for any reasons.
Entry 2: Daden Limited, David Burden ([email protected])
Name of System: Halo
Description of system: Halo is an automated avatar running within the Second Life virtual world. As well as
being able to talk to users, navigate, and exchange objects/money, our current focus is on giving Halo emotions. Halo can
learn emotional responses for objects and avatars based on their behaviour, and from talking to other users, as well as by
programming. By existing (and having agency) in a rich virtual world designed for humans not computers, having a
visual look identical to human users of the world, and integrating several different AI technologies, Halo provides an
innovative new way to explore artificial intelligence.
Entry 3: Middlesex University, Chris Huyck ([email protected]; www.cwa.mdx.ac.uk/CABot/CABot.html)
Name of System: CABot2
Description of system: CABot2 is an assistant to a user in a simulated 3D environment. It is an agent in the
environment along with the user; it accepts commands from the user, views the environment, maintains its own plans and
emits actions. CABot2 is entirely implemented in simulated (fatiguing Leaky Integrate and Fire) neurons. The
commands are interpreted by a natural language parser that is a sound psycholinguistic model, and the initial parts of
vision are a reasonable approximation of the human retina and primary visual cortex. CABot2, the second prototype in
the CABot project, also learns simple actions.
Entry 4: De Montfort University, Martin Rhodes and Simon Coupland ([email protected], [email protected])
Name of System: Pro Evolutionary Soccer
Description of system: Video games are the new frontier in machine intelligence. Gamers want to play against
truly human like players that make rational decisions and make mistakes in the same way a human would. ProEvolutionary soccer demonstrates machine intelligence through a football video game application. The current generation
of football video games suffer from a predictable, repetitive style of gameplay. Pro-Evolutionary soccer uses a stochastic
approach to give varied, organic style of play in the form of free-kick taking. Given a physics model and the positions of
the opposing team, our system finds a near optimal free kick from all possible free kicks giving a varied and challenging
gameplay.