Patreon Exclusive Content - Revision history

Chili: /* SlideFucker 3000 */

2018-06-10T15:41:47Z

‎SlideFucker 3000

2018-06-10T15:32:52Z

‎ASM and Chill with Chili

2017-09-21T05:04:46Z

2017-09-21T04:51:35Z

2017-08-31T14:03:25Z

‎SlideFucker 3000

2017-05-27T11:41:57Z

‎SlideFucker 3000

2017-05-27T11:15:05Z

‎SlideFucker 3000

2017-05-27T11:14:11Z

‎SlideFucker 3000

2017-05-27T11:13:46Z

‎SlideFucker 3000

2017-05-17T14:44:52Z

‎SlideFucker 3000

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 |- style="background-color:#333;color:#c1c1c1;"
 | style="border:1px solid grey;padding:8px;" colspan="6" | In this video we modify the solver to break the problem down into smaller sub-problems. We do this with a sexy heuristic functor system that allows us to swap out different functors, as well as a sub-problem mapper. The is the last video on the AI solver logic.
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 | style="border:1px solid grey;"|Dec 28, 2016
 | style="border:1px solid grey;"|1:22:00
-| style="border:1px solid grey;"|$0
+| style="border:1px solid grey;"|$2
-| style="border:1px solid grey;"|PUBLIC
+| style="border:1px solid grey;"|No
 |- style="background-color:#333;color:#c1c1c1;"
 | style="border:1px solid grey;padding:8px;" colspan="6" | In this video Chili reacquaints himself with TASM and x86 assembly, going over the basics of setting up a .asm source file, and calling some system services (BIOS int 10h, int 16h, DOS int 21h). We then mess with some looping and counting, defining some global data and getting pointers (offsets), and then we go all the way in and do some real calculations, fucking shit up real good along the way. But debug.exe has got our back, and we squash the bugs while also showing you guys the machine code being executed instruction by instruction by the CPU, and how it affects the state of the registers and RAM. [[ASM and Chill with Chili 1|Click here for the page for this tutorial.]]

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 == SlideFucker 3000 ==
-In this series Chili endeavors to create an AI agent in C++ that can solve a classic puzzle game (8/15/24 sliding puzzle). This agent will not only solve the base problem, but will also be able to use computer vision to read the puzzle state from the screen (with OpenCV), and use input automation to enter the solution into the game (with AutoIt). There will be no reversing/process manipulation involved; the agent will be required interact with the game just as a human user would.
+In this series Chili endeavors to create an AI agent in C++ that can solve a classic puzzle game (8/15/24 sliding puzzle). This agent will not only solve the base problem, but will also be able to use computer vision to read the puzzle state from the screen (with [http://opencv.org OpenCV]), and use input automation to enter the solution into the game (with AutoIt). There will be no reversing/process manipulation involved; the agent will be required interact with the game just as a human user would.
 Check out the [https://www.youtube.com/watch?v=ugujLVv_k2E Mission Statement video] for more infos.

@@ Line 5: / Line 5: @@
 == SlideFucker 3000 ==
 In this series Chili endeavors to create an AI agent in C++ that can solve a classic puzzle game (8/15/24 sliding puzzle). This agent will not only solve the base problem, but will also be able to use computer vision to read the puzzle state from the screen (with OpenCV), and use input automation to enter the solution into the game (with AutoIt). There will be no reversing/process manipulation involved; the agent will be required interact with the game just as a human user would.
 {| style="border:1px solid grey;border-collapse:collapse;width=100%;"

@@ Line 59: / Line 59: @@
 |- style="background-color:#333;color:#c1c1c1;"
 | style="border:1px solid grey;padding:8px;" colspan="6" | In this video Chili implements the A* heuristic search algorithm to find optimal solutions for the sliding tile puzzle game. Mistakes! They were made! Bugs were also eliminated with extreme prejudice. But just when you think you're out... they pull you back in!
 |}

@@ Line 58: / Line 58: @@
 | style="border:1px solid grey;"|NO
 |- style="background-color:#333;color:#c1c1c1;"
-| style="border:1px solid grey;padding:8px;" colspan="6" | In this video Chili implements the A* heuristic search algorithm to find optimal solutions for the sliding tile puzzle game. Mistakes! They were made! Bugs were eliminated with extreme prejudice. But just when you think you're out... they pull you back in!
+| style="border:1px solid grey;padding:8px;" colspan="6" | In this video Chili implements the A* heuristic search algorithm to find optimal solutions for the sliding tile puzzle game. Mistakes! They were made! Bugs were also eliminated with extreme prejudice. But just when you think you're out... they pull you back in!
 |}

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 |- style="background-color:#333;color:#c1c1c1;"
 | style="border:1px solid grey;padding:8px;" colspan="6" | In this video Chili finishes the board capture by parsing the positions of the tiles on the board. We create a new data type <code>BoardPosition</code> that will form the core of the AI solver, storing captured/explored board positions and providing a suite of fundamental operations thereon. At the end of this video, there is a brief discussion on the AI routine (A* heuristic search) that we will be using to solve the problem, setting the stage for Part 4.
 |}