Super Sanity

I am now in possession of LittleBigPlanet, and have been for a few days now. It’s a fun game. However, there is one problem I am having with it. I want to create a level, but whenever I do, I freeze up with all the options presented to me. I don’t know where to start.

However, I recently got a couple of ideas that could be used:
- A crane-like vehicle which has a grabber. The grabber can grab stuff and release it whenever the player chooses. It could be used in a 2P puzzle where the crane grabs a hanging grabble, attached by an elastic cord. The crane grabs the grabable material and moves back to create tension on the elastic cord. Then it releases it, sending the material flying in the other direction. Due to screen size, this might have to be done in a vertical direction.

- Another idea is a cannon device thingy. Here’s a diagram: . Could be used for blasting away at material covering parts of a level. Also, it could be a sentient enemy.

- Some possible levels I’ve thought of include a fairground level (runaway Ferris wheel, whack-a-mole, haunted house, etc), a martial arts dojo (hanging on to a kick which sends Sackboy flying), and a level based on old skool videogames (Pacman, Tetris, Q-Bert, etc).

This post is mainly a reminder for myself, should I forget these ideas.

On Wednesday the 29th of October I submitted my final report for my Honours project. One years worth of work condensed into a 50 page report. It was a long run, but it was fun.

Next thing on the agenda is some summer research. I’ve received a summer research scholarship in which I perform research for 10 weeks on a topic. My topic that I was given is basically extracting information from Wikipedia and storing it in a logical database known as Cyc. Cyc’s goal (look it up on Wikipedia. Oh the irony) is to create an artificial intelligence that is made up of common sense and can understand human emotion and stuff. I’m still a little hazy on it’s exact definition but I’m sure that I’ll grow to know it well.

And after that is hopefully a PhD in which I can further explore the application of reinforcement learning. I hope to create an agent capable of learning anything from any sources (Cyc, by example, by self-exploration).

Anyway, here’s 2008 Honours Final Report. There should be another copy of it up somewhere on the University of Waikato site, probably in the Greenstone database.

I was viewing the results today as I complied them into a LaTeX graph, and it showed that SmartAgent 1.3 was significantly worse than V1.2. Strange, I thought. Hell, it was about as good as 1.1. Then I realised that long ago, I had left a bug in the 1.3 code that got ironed out in 1.4.

This bug has appeared in every version prior to 1.4 so I fixed it and now I have to recollect the results. It shouldn’t be too big a deal, as each agent is pretty fast and the results should be done in a day or so.

It’s been a while. So long that I’ve forgotten what it is that the console and GUI trainers do. I need to recall this for details about them in my final report. Which, if you’re interested is coming along well. Although I don’t have time to dilly-dally as I have little free time at the moment.

Anyway, consoleTrainerJava does this:
Spits out the number of steps per episode and ther total number of steps for all N episodes.

guiTrainerJava does this:
Well, I can’t get it working… Figures. Anyway, from a single, possible misinformed screenshot, it shows the current episode number, as well as the number of steps for this episode and the total steps passed dince stared. It also says the current piece. I’m not sure about this last bit, but I think it also states the number of lines completed. It could be total reward but I’m unsure.

Haven’t updated my progress in a while. Anyway, I just thought I’d consolidate my thoughts online so I can remember what I need to do for my final report.

For the results, I’ll need to modify my graph colour scheme to be document friendly or simply show the graphs with gnuplot. I might do that as it’s already optimised for LaTeX.

The experimental performances have to be chanegd to match the style in the competition so I can have my own mini-version comparison competition.

WEKA has to be discussed, with it’s applications of being a static comparison as well as an incremental help.

I should hit up the other competitors again for a summary of their strategies or something if I can.

Got a test now, so gotta go!