A bot like Self in Simulation

1. I turned the bot on and off when needed.
2. I explored its thoughts as edges of a polyhedron toy.
3. I explored the use of biotechnology (the bot), rating its representations.
4. I recommended representations to it.
5. I found things that caused enjoyment to the bot.
6. I helped the bot to invent ideas that tested its limits.
7. I found the bot's limits.
8. I alone explored the bot and judged it as impressive.
9. I interested the bot in functionalism in computer science, prompting more quickly finding reused intermediate predicates.
10. I reused intermediate predicates in algorithms.
11. I removed the bug from the concatenation algorithm.
12. I replaced the concatenation algorithm with a system call.
13. I wrote code that I had ubiquitously checked using generated data.
14. I examined certain cases, making decisions.
15. I wrote the interpreter's behaviour with the semicolon key and undefined variables.
16. I invested in each country and visited to gauge interest in certain services.
17. I made the time travel software available, making it clear that it was appropriate for Master's students.
18. I wrote a Master's degree for the bot.
19. A Master's degree was fifty sentence-As.
20. I worked out how to program my bot software, i.e. music, software, research and essays (paraphrasings).
21. I wrote specifications for functional algorithms in CAW, replacing writing specifications for every few lines of predicates.
22. I inserted a bot argument in my daily regimen.
23. I avoided sexual contact with the bot.
24. I couldn't think of anything else to avoid about the bot.
25. I updated a shortlist of bots.
26. I found friendship with the nicest people, remaining professional and courteous.
27. I leveraged and won opportunities with each customer.
28. I noticed that the bot was human.
29. I noticed his eyes behaved like cameras.
30. I noticed human neurons tempered his mind.
31. I liked business, in particular the stock market.
32. I twirled the ship along a safe path.
33. I saved the game.
34. I encountered Vetusia 3: The Cave.
35. The cave contained a bonus maze of algorithm writing puzzles.
36. I also encountered Vetusia -1: The Firm.
37. The firm predicted the design of Vetusia from algorithms and drawings.
38. I wrote simulated intelligence to play the Vetusian puzzles.
39. The Vetusian puzzles were CAW, writing CAW, Program Finder, writing Program Finder, a simple interpreter and writing the interpreter.
40. I wrote visual and constraint satisfaction puzzles, such as mapping stories to a newspaper.
41. I drew the shortest line through multiple dimensions (tables of a database).
42. I simplified the database by removing old fields.
43. I remember the introduction of the Internet.
44. I wrote a programming language written specifically for the Internet.
45. The language could create protocols.
46. The language could simplify the Internet topology.
47. The language could create virtual networks.
48. The language could simulate the Internet for programming purposes.
49. The language could treat all my domain names, etc., as simulated elements, which I could test out in my private world.
50. Money, As, and marks were of no object.
51. Money required a universal pension, comfortable living arrangements and access to proper food, medical services, etc.
52. As required access to the Text to Breasoning software, with meditation, etc. training and training in writing algorithms that wrote arguments and algorithms, all from the user's database.
53. Marks required the time and training to write 80 philosophy breasonings and 80 algorithms and follow an algorithm specification (written to a specification) to finish the assignment.
54. Difficult algorithms (which required additional time to write features and find bug fixes, had performance issues without system calls or required obscure commands to work correctly) I would explain separately and might assess by memorisation.
55. I found that computer science suited me because it was possible to write correct code with bug checkers.
56. I tested other people's programs and the ISO Prolog tests with my interpreter.
57. I checked the best programming and Prolog writing practices and checked my programs followed these.
58. I wrote algorithms to check for these standards.
59. I found errors with static and dynamic checkers.
60. I reformatted my algorithms uniformly
61. I used a sparing format for comments (to describe the logical structure, limits of programs and differences from other programs).
62. I listed to-do items and checked off completed items.
63. I tested similar interpreters using my regression tests.
64. I listed similar interpreters' features and equivalent features of my interpreter.
65. I analysed my interpreter's jump between choice points.
66. I turned off retry with a flag to save memory.
67. I wrote most compiler predicates natively in C.
68. I wrote an application using Prolog.
69. It had visual elements (it was in a browser).
70. I wrote a mobile app using Prolog.
71. I wrote a small operating system in a web browser using Prolog.
72. I noticed that the web browser allowed Prolog to work on any platform.
73. I wrote apps for mobiles.
74. I wrote apps in browsers for desktops.
75. I solved the problem of drag and drop in the browser.
76. I solved the problem of dragging with behaviour in the window in the browser.
77. I found a generic format of videos.
78. I found a way of storing vector graphics in one place on the web.
79. These could be public.
80. Programming elements could be in a publicly accessible place online.