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Playing Pinball using Human Level Artificial Intelligence

 

     

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This video shows a robot playing a pinball machine. There are no sound in the video because I wanted to show the viewers what the robot is thinking while playing the game. The flashing text and freeze frames are the internal thoughts of the robot and not instruction text for the viewers. These internal thoughts describe the details of how the robot produce intelligence.

My robot doesn't use: planning programs/heuristic searches (used by MIT and Stanford University), Bayesian's probability theories for decision making, Bayesian's equation for induction and deduction, semantic networks for natural language understanding, predicate calculus, common sense systems, first-order logic, rule-based systems, genetic programming, or MACHINE LEARNING.

When playing pinball, the robot has to understand how balls roll on flat surfaces, like in a pinball machine. Based on past experiences, the robot knows how a ball rolls on a flat surface and how gravity affects its speed, direction, and physical properties. This information is important because the robot needs to predict the future path of the ball when playing the game. By understanding where the ball will be in the future, the robot can set up strategies to hit the ball in a certain direction. For example, if the robot wanted to hit the ball into a small hole, he has to predict the future path of the ball, and identify where to hit the ball using pivoting flippers.

In the game of pinball, the objective is very simple: keep the ball in play for as long as possible. The longer the ball is playing the more points the player accumulates. If the ball goes into the pit areas, then the player loses. These rules are constantly being followed by the robot while playing the game. The robot is also doing other things, like formulating strategies to beat the game. He will keep the good strategies and eliminate the bad strategies.

What is remarkable about this robot is that it can play any pinball machine, regardless of environment. He can play a really complex pinball machine with lots of twists and turns or play a simple pinball machine. If the rules and objectives of the game are changed, the robot can still adapt to the environment and play the game. For example, if the gravity of the pinball machine was changed -- let's say someone tilted the machine at a 45 degree angle instead of a 15 degree angle, the ball will be rolling much faster. The robot can compensate for that change and still play the game.

On more thing i have to mention is that the internal thoughts of the robot, the text that flashes in the robot's mind are actually sound text. Normally, the robot's brain is given diagrams, symbols, and arrows to suggest an action. The robot's mind isn't presented with a perfect english sentence. Only bits and pieces of words are given (usually in the form of pictures). Based on these simple pictures the robot will know what to do. For example, if the robot was given this instruction: "wait for the ball to touch the yellow area before pressing the A button". The robot's mind might show a yellow line on the left flipper and an arrow pointing to the ball with a press A button on the side. This fabricated animation is the meaning to the sentence and is most likely to activate in the robot's mind. In other words, instead of a complete sentence being activated in the robot's mind, a simple fabricated movie is activated. This fabricated movie represents the meaning to the sentence. Also, in the robot's mind, facts and knowledge are presented in a gibberish manner, whereby the sentences are not complete sentences, but important words flashing in sequence order.

         

 

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