Artificial Intelligence play tetris (displays robot's thoughts)
IBM's deep blue project can only play chess, an autonomous car can only drive a car, an AI checkers program can only play checkers. A universal artificial intelligence is one software program that can do any human task. It can drive a car, play chess, play any video game, cook in a restaurant, clean a house, fly a plane, write software programs, etc.
So far I have made videos on playing chess, playing video games, driving a car, and doing math equations. I stated in my books/patent apps/website, that my robot can do any human task. This video shows the robot playing tetris. In the video I show how the robot thinks while he's playing the game.
Tetris is a puzzle game that require the player to stack up blocks to form stacked rows. Humans learn how to stack up blocks and solve puzzles starting from a very young age. Stacking blocks so the pieces fit are lessons learned in Kindergarten and in grade school. When the robot is playing tetris, he has to tap into knowledge about block stacking or puzzle stacking. He has to know that this shape fits into that shape.
In addition to knowledge about piecing together puzzles, the robot has to have strategies to play the game. He has to have objectives, and recursive objectives and so forth. These objectives and strategies are discovered through either trial and error or from instruction manuals. The robot can read strategies from a video game magazine or he can discover strategies based on trial and error.
Also, making decisions about where should blocks be stacked and conflicts of interests are learned from teachers in school. By the time the robot is at age 10, his brain contains self-learning pathways or self-adaptive pathways. He has the knowledge to teach himself the best strategies to play tetris. For example, no teacher has taught the robot how to play tetris. He used his own intelligence to find out what the game is about, how to play the game, what are the best strategies in the game, what decisions to make, and so forth.
The truth is that playing tetris is a very complicated thing to do. The video only shows a general way the robot thinks as it is making decisions in the game. The internal instructions are much more complex.
This robot doesn't use planning programs or heuristic searches. This is not an expert program that was designed specifically to play tetris. This robot can play chess, play checkers, play monopoly (or any board game), drive a car, fly a plane, play any video game, or do any human task. Programmers don't have to change the robot's brain for each human task.
For more information about human level artificial intelligence, visit my website:
http://www.humanlevelartificialintelligence.com
tags:
human level artificial intelligence, ai, artificial intelligence, artificial general intelligence, true ai, strong ai, human level ai, cognitive science, ai plays video game, robot plays video game, agi, digital human brain, human intelligence, human brain, human mind, robot thoughts, deep learning, human thoughts, ai plays role playing games, ai play rpg, demo ai, general ai.
IBM’s deep blue project can only play chess, an autonomous car can only drive a car, an AI checkers program can only play checkers. A universal artificial intelligence is one software program that can do any human task. It can drive a car, play chess, play any video game, cook in a restaurant, clean a house, fly a plane, write software programs, etc.
So far I have made videos on playing chess, playing video games, driving a car, and doing math equations. I stated in my books/patent apps/website, that my robot can do any human task. This video shows the robot playing tetris. In the video I show how the robot thinks while he’s playing the game.
Tetris is a puzzle game that require the player to stack up blocks to form stacked rows. Humans learn how to stack up blocks and solve puzzles starting from a very young age. Stacking blocks so the pieces fit are lessons learned in Kindergarten and in grade school. When the robot is playing tetris, he has to tap into knowledge about block stacking or puzzle stacking. He has to know that this shape fits into that shape.
In addition to knowledge about piecing together puzzles, the robot has to have strategies to play the game. He has to have objectives, and recursive objectives and so forth. These objectives and strategies are discovered through either trial and error or from instruction manuals. The robot can read strategies from a video game magazine or he can discover strategies based on trial and error.
Also, making decisions about where should blocks be stacked and conflicts of interests are learned from teachers in school. By the time the robot is at age 10, his brain contains self-learning pathways or self-adaptive pathways. He has the knowledge to teach himself the best strategies to play tetris. For example, no teacher has taught the robot how to play tetris. He used his own intelligence to find out what the game is about, how to play the game, what are the best strategies in the game, what decisions to make, and so forth.
The truth is that playing tetris is a very complicated thing to do. The video only shows a general way the robot thinks as it is making decisions in the game. The internal instructions are much more complex.
This robot doesn’t use planning programs or heuristic searches. This is not an expert program that was designed specifically to play tetris. This robot can play chess, play checkers, play monopoly (or any board game), drive a car, fly a plane, play any video game, or do any human task. Programmers don’t have to change the robot’s brain for each human task.
For more information about human level artificial intelligence, visit my website:
http://www.humanlevelartificialintelligence.com
tags:
human level artificial intelligence, ai, artificial intelligence, artificial general intelligence, true ai, strong ai, human level ai, cognitive science, ai plays video game, robot plays video game, agi, digital human brain, human intelligence, human brain, human mind, robot thoughts, deep learning, human thoughts, ai plays role playing games, ai play rpg, demo ai, general ai.
