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Embedded and Microcontrollers
Embedded Forum Video games; making us better engineers (mini Halo Reach review)
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Video games; making us better engineers (mini Halo Reach review)

Catwell
Catwell over 15 years ago
"Action game players make more correct decisions per unit time."
 
Probably the single best excuse for playing video games. This quote comes from UR professor of brain and cognitive science, Daphne Bavelier. In a recent study, she has found that action gamers are up to 25% more likely to come up with correct answers to questions faster than people who do not play such games. The perceived reason Bavelier attributes to the performance boost comes from the heightened sense of surroundings that action gamers have while playing.
 
This is a great excuse I can make for playing Halo Reach until 3:30 am today, launch day for the game. I was improving my decision making skills! Side note, the game is very fun. I was expecting stellar graphics, and they were good, by Xbox standards. I was hoping that Reach would rival PC games, but it does not unfortunately. See my suggestion on improving Xbox graphics.
 
Bavelier goes on to say that the reaction time, accuracy, isn't just limited to visuals, but in also audio tests. The process of making a right choice is called probabilistic inference. The brain collects bits of visual and audible information and calculates what is perceived as the best choice. "Decisions are never black and white," she said. "The brain is always computing probabilities. As you drive, for instance, you may see a movement on your right, estimate whether you are on a collision course, and based on that probability make a binary decision: brake or don't brake."

You can read more about the study in a future journal of Current Biology. In the mean time, see the school page on the study. Authors of the study; Daphne Bavelier, Alexandre Pouget, and C. Shawn Green show how a regimin of video game playing could improve your reaction and decision making. But, regular gamers already know this, right?

Cabe
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  • Former Member
    Former Member over 15 years ago

    Hi Cabe

     

    Very interesting information and a great excuse for playing games!

     

    Whilst studying for my Masters in Neuroscience, I discovered that although the brain seems to work in a probabilistic way, it is more accurate to describe decision making in the brain in terms of a sum of weighted inputs. Each neuron takes a very small part of the decision based on its inputs - some conributing negatively and some positively, with each neuron being a part of a neural network which will produce a generalistic answer, e.g., there is a 30% chance that child 200 yards ahead will step into the road. Creating a model or function for this behaviour is so complex that artificial neural networks are often termed as 'black box methods' as you may get an answer, but you're never sure how it was really reached. I believe Professor Bavelier may have simplified this process somewhat! image

     

    I hope this might interest someone

    Philip

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  • Catwell
    Catwell over 15 years ago in reply to Former Member

    Philip,

     

    Do you think artificial intelligence, on a child level at least, is anywhere near being possible? Thoughts on the subject?

     

    Cabe

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  • Former Member
    Former Member over 15 years ago in reply to Catwell
    I think that if you do enough research on your particular interest area you can come up with reasons as to why your area is the best. It is all to do with marketing, afterall that's why we have marketing in any large company, right?
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  • Former Member
    Former Member over 15 years ago in reply to Catwell

    Cabe,

     

    It all depends on what you mean by "on a child level" and on the application. If you want to run a neural network to sniff out illegal drugs from coffee or detect the presence of an object in a field of view or detecting audio patterns / frequency components from a sound source, these can all be performed. However, putting all this together by modelling auditory, visual, muscle motor movement, touch etc. with a neural network is hard enough, but trying to model how a child thinks - well, I have two of these real children and how you could produce AI to compete with them is a complex task. In the end, I guess it would eventually become possible, but philosophically, would you have a child?

     

    Philip

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