Time flies when you’re working on stuff…
The good news is that I have a demo coming for Interrogative AI, so that you can play with it. The bad news is that it’s not ready today. The good news is that the bad news is because it’s a multiplayer game with RPG capabilities. Because a static demo was just way too easy for me! The bad news? It’s still not ready today 
Have a screenshot:
AI Works of late…
Roguelike-style demo for Interrogative.
It’s nothing too special (for now), but this will serve as the world that my Interrogative AI will inhabit. Richer in data than visual content, this demo will be a proving ground for a lot of the AI that I’m working on. And speaking of which…
More language AI…
A lot of the research I’ve been doing into AI lately has been trying to look at more generalized AI- though not the “strong-” or “general-” AI that most people might be familiar with. Instead, I’m looking into a more adaptive AI that seems like strong or general AI, but is really more like a flexible system that allows for extensions of its domain knowledge, using Semantic Data.
To that end, I’m looking at doing a few experiments with data using some semantic techniques, in the hopes of developing some lightweight algorithms that can be leveraged in game AI to give the NPCs a lot more fluidity in how they interact with players and the game world. A few of those experiments involve creating a formalized language dictionary (English, for now) that will allow the AI to use language in a more flexible manner than simply being given Dialog Templates or standard statements. We all know how to use words, and we have dictionaries that tell us how to use even more words. AI shouldn’t be stuck out in the cold when it comes to understanding words.
World modeling…
Another issue that I want to tackle in AI is that of how the AI interacts with the world. One thing that humans (and animals) do is create an internal model of the world around them. This model is constantly updated it as we move about, doing things, and gathering feedback. Internally, you know that if we knock a glass off of the kitchen table onto a tile floor, it’s probably going to shatter. We know that if we do the same, but the floor is shag carpet, then it might not shatter. Our brain doesn’t need to model physics in any complicated way to know that. It just simply knows that the glass will fall, and come apart on impact, because the tile floor is hard. Within our minds, that’s a general rule: Glass stuff hitting (or hit by) hard things will break.
Our brains store those rules as facts. Some of those rules and facts are shoddy because they’re based on our limited senses of observation. We do with what we got, and sometimes it’s a bit off.
So easy a baby can do it…
It’s simple, right? Too simple. I remember watching my daughter teaching herself how to sit in these kid-sized folding chairs we bought our kids. My daughter didn’t need 10 million sets of data to learn how to sit on the chair. She adjusted on the fly, knew what the end result should be, and learned that the folding chair was not the same as sitting on a box, couch, or bed. After a second try, my daughter had mastered the chair. After that, she knew that those chairs are different, and her mind built rules on the fly for how to treat them. The rules she formed are based on knowledge gained at first by classification similar to Machine Learning, and encoded as Semantic Data in her brain.
Machine Learning is currently pretty bad at anything much more complicated than classification. In my opinion, ML is not even AI because it doesn’t even try to avail itself of any understanding of the world it inhabits. It builds no world model, and if the data that its been fed changes suddenly, then it needs tons of that data to readjust. For the domains they’re trained on, ML works really well. I think that’s great. But it’s just way too narrow in scope. It’s a great tool. But it’s just a tool.
Conclusion…
Semantic AI is where it’s at.
You might think that that was something of a departure for me from game AI to techniques that do more complex things. But in my mind, these techniques should naturally be lightweight compared to what we’re doing now. Games benefit from having faster, more realistic AI.
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