Neural Networks Reinforcement Learning

Learning from Games

I don’t need to tell this audience about the momentum building behind educational games.  Even when I was an elementary student, going to the computer lab to play Math Blaster, Odell Down Under, or Oregon Trail was a special treat.  These days, kids grow up on video games: game consoles are nearly as common as TVs in households; cell phones are standard issue for kids of all walks of life; the internet is available to everyone, with its countless easily accessible, free games.

The Kodu just wants to visit the castle.

Perhaps the most significant indication that games are becoming an important part of everyday life is the fact that many web ads are microgames.  While they are usually unsophisticated, these game ads are telling for two reasons.  First, they indicate what everyone has known all along: games are fun and engaging, and people enjoy the opportunity to participate in their entertainment.  Second, and possibly less obviously, it indicates that people’s understanding of games is broadening and deepening.  Games are no longer simply about having fun.  People actively absorb information from games they play, and more and more people have the literacy necessary to do so quickly and easily.

Of course, games can communicate information in some ways more effectively than others.  Do you remember the which product the last advergame you played was about?   I would guess no, but I would also guess that you do remember some things about the game, such as how to play it and how cheesy the graphics looked.  When I think back to my Math Blaster days, what I remember best is that the rocket pack level was the coolest.  And when a facebook version of Oregon Trail came out a year or two ago, I still didn’t know how to keep my party members alive, even though they were my friends this time.

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2002-02-09 14:24:25 by on-trial

The amount of poor and self-interested advice that is being issued by brokerages and their analysts. To this day, the majority of stockbrokers are compensated on the number of trades their customers make, not on the returns they generate for them or on the quality of the advice they provide. We believe that the price targets and analyst ratings are made with several masters in mind, none of whom are the individual investor. In a similar fashion, sell-side stock analysts are generally compensated based upon the overall profitability of their firms, not the quality or accuracy of their analysis. In the end, analysts have minimal structural incentive to be accurate in their predictions; rather their built-in incentive is to be as favorable to their corporate clients as possible. It is a...

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