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Re: No subject |
Jun 30, 2008, 16:58 |
Fang |
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So, if each user is a simulator training your A.I., how does it remove the processing burden from the end user?
It's removing the higher level planning from the end user. Today's games don't have very much of it, because of CPU limitations.
The end user is still running the physics simulator (hopefully running much faster on the graphics card) and managing the game world. The point of this isn't to free up CPU cycles on the end user, because very little of it is being used for higher-order planning. It's to provide something that isn't being done (or only in a very limited fashion) right now.
You are now contradicting yourself from earlier, this is no-longer real time with regards to gameplay.
You only think this because you don't understand how reinforcement learning works.
The model-based controller in the helicopter is running in real time. In the same way, the software agents in the end-users game would be running in real time. Don't confuse the learning process with action process. The action process response from the central AI server (the "here are my observation what should I do") can occur very quickly, especially since the goal isn't to give a truly optimal answer, but instead a best guess given the current learning level. It's the equivalent of a database query. The learning process (which took a day with the helicopter example) is about generating a higher order plan that does something truly intelligent, like fly a helicopter upside, or respond to an ever changing tactical situation. This occurs in the central AI server farm, so it doesn't have to be done for each user. This is where you get all of your processing savings compared to the current inefficient design.
At first, the game's agents probably won't be that smart. But with 100,000 simulators, the central AI server would probably start giving very intelligent actions pretty quickly.
Kind of like the Folding/SETI@Home programs. The more systems you have, the faster you can solve the problem.
Think of it this way. Do you remember the Sony AIBO? The little robotic dog they made? Each dog, when it comes out of the box has a limited controller that is passable for what people expect. Kind of like today's games. Now if each of these dogs were networked with a central server, the central server can issue the policies for how it thinks the controller should behave. This occurs very quickly and with little overhead. It will take time for the actions to truly become intelligent, but the dogs will work, and the games will play. If you had 100,000 dogs working at the same time, it would happen very quickly.
Of course, there is a exploration vs exploitation tradeoff, but I won't get into that.
Since most single player games have already been designed to run with a multiplayer server, there really isn't that much more overhead you are adding to the user client. And unlike in a multiplayer game, you can continue to let the client handle the gameworld physics.
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Date |
Subject |
Author |
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1. |
Jun 28, 10:50 |
No subject |
xXBatmanXx |
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2. |
Jun 28, 13:20 |
Re: No subject |
Syntarsus |
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3. |
Jun 28, 13:33 |
Re: No subject |
Fang |
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4. |
Jun 28, 15:21 |
Re: No subject |
Enahs |
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5. |
Jun 28, 15:42 |
Re: No subject |
Enahs |
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6. |
Jun 28, 21:45 |
Re: No subject |
Jerykk |
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7. |
Jun 29, 00:48 |
Re: No subject |
Fang |
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8. |
Jun 29, 12:22 |
Re: No subject |
Enahs |
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9. |
Jun 29, 16:38 |
Re: No subject |
Fang |
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10. |
Jun 29, 17:57 |
Re: No subject |
Enahs |
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12. |
Jun 29, 22:34 |
Re: No subject |
Fang |
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13. |
Jun 30, 08:30 |
Re: No subject |
Enahs |
| >> |
14. |
Jun 30, 16:58 |
Re: No subject |
Fang |
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11. |
Jun 29, 19:52 |
No subject |
Mr. Tact |
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