It is interesting. You the readers are coming in on the middle of the story. I have been working on this stuff for about 20 years, and so any time I have new developments to report, they exist in my mind in a context of much work having been done before. However you are coming in in the middle of the story, so it is catch as catch can whether you will understand what I am saying at one time or another.
Understand what you can. Don't worry about what you can't. It's probably because I have not provided enough context. I provide as much context as I can bear for every article, and try to put a little more in later as I read the articles. If you have questions or do not understand something, I would very much appreciate your comments or questions. Thank you.
When making a Model so that a computer can understand English, one thing you must keep in mind as you work, is to come up with parameters that a computer can understand. The approach I take is categorization with the goal of creating a Rule of Twenty Profile. You can categorize words to your hearts content, but you have to remember to make the categories things that a computer can process. So as I come up with charateristics for the profile, I need to make sure a computer can use them.
For example, I am presently building a 'plural' category/characteristic.:
I have this crazy idea that I can apply the Rule of Twenty Profile System to create a profile for every English word, and therefore have a computer generated character be able to both understand and compose dialog. Actually, I used the Rule of Twenty with D&D spells once so I know that a fairly high level of conceptual complexity can be managed (then the system collpased into six variables showing that there wasn't much to the spell system). I don't work with spells any more since they are evil, but I think that this effort with English has a tiny slight chance of working.
If the chance of succeeding is for example 1% then it's worth a shot. Even if it doesn't work I'll be able to demonstrate how I put together a rule of twenty system.
I have been beating up on a group of about 5000 common words for four months now. The first thing I did was set up a four bit binary system to identify part of speech. Here are the results of my first two phases:
About 20 years ago when I first started thinking about Artificial Creativity as a field, I produced the following diagram to describe it:

One approach to Artificial Creativity is to have the users of software do the creating. For reason which I have touched on and hope to focus an article on some time, I think it's important to have as many people as possible involved in making creative systems. I think the users of computer systems should do it, but to have users do artificial creativity requires two needs:
Here is my design for a terrain generator. Artificial Worlds need terrain. This terrain generator design is not finished but the part that is finished I can show. The world is divided into a cube of six sides. Each side is covered with regions of terrain. Each region has a center and a size. There are a few large regions like the poles that have a very large size. Most regions are smaller - continents, islands, oceans, forests, mountainous areas etc. The data kept for each region is size, type of terrain, game significance. I will leave off game significance for now. Regions overlap producing complex terrain.
| Letter | Terrain | 'Opposite' | Color |
| A | Arctic | Tropical | whiTe |
| B | Bedrock | Eolian | Neutral gray |
| C | Cities / Civilized | Hunters | blacK |
| D | Desert / Dry | Rainy | Orange |
| E | Eolian (dirt) | Bedrock | Faded brown |
| F | Forest | Q-swamp | Jaded Jade |
| G | Green / Fertile | Infertile | Green |
| H | Hunters | Civilized | Saturated Salmon |
| I | Infertile | Green | Purple |
| J | Jungle / Thicket | Open | Quixotic chartreuse |
| K | K-farms / farmers | Nomads | Murky Mustard |
| L | Lake / Fresh water | Sea | Achromatic Aqua |
| M | Mountain | Plain | Red |
| N | Nomads | K-farms | Cold Cyan |
| O | Open | Jungle | Dark olive |
| P | Plain | Mountain | yEllow |
| Q | Q-swamp | Forest | Infuscated Indigo |
| R | Rainy / Rainforest | Desert | Light Lavender |
| S | Sea / Salt water | Lake | Blue |
| T | Tropical | Arctic | Hot pink |
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