(Nintendo DS) The Legend of Zelda: Spirit Tracks is a beautifully crafted game where the gameplay, music and artwork complement each other to create an engaging world that you don't want to leave. I have a couple of major issues with the game, but apart from these gripes I absolutely love the game and would recommend it to many people, including my Mum. Read more...

(PS3) This latest offering from Quantic Dream was years in the making and is well worth the wait. The game uses the PS3 fully, pushing it to levels I didn't know were possible in games. You are plunged into a realistic world where your actions will help save a boy from a serial killer, or let the serial killer escape justice. Although you are forced to do many boring mundane tasks, the game is an amazing step into interactive drama on a scale that hasn't been seen before. Read more...

(Nintendo DS) Most puzzles are very simple since this game is probably aimed at the pre-teen market, but there are a few that have suitable challenges. The story is solid and encourages you to complete just one more puzzle, get past just one more puzzle and therefore improves the addiction of the game. Read more...

While working at DSTO (Defence Science, Technology Organisation), I initiated a series of tests using Quake and Unreal Tournament 2004 as a Turing Test. The goal of this work was to determine what game players use to distinguish computer-controlled players (Bots) from human players in order to determine areas that Bots needed to improve. Initial results are described in a DSTO technical report (PDF). I also presented further results at the Academic Summit of the Australian Game Developers Conference 2004. The academic summit talk can be downloaded as a PowerPoint show. The work required organising 30 people into tournaments and making sure they did not know the number of computer controlled characters that they were playing against.

My masters thesis aimed to create characters that adapted, used context and were individuals (i.e. different to the other characters even when their initial personality templates were different). In order to test these three areas I looked at the choices the characters made (i.e. what they did), how well they thought they were achieving their personal goals (which was used as their context) and I developed a quantitative measure for individuality. Eventually the theory that you can develop "different" characters using my techniques would need to be tested using human participants and asking them whether they notice differences. As a preliminary step before this, a quantitative measure determines whether there are any statistically significant differences between the characters. If the characters have no statistical differences, then it is very unlikely that humans would notice the difference. This means that the quantitative test needs to be passed prior to testing with human participants. Due to this, there were no human players in the tests performed.

The quantitative measure for individuality that I developed is based on paired t-tests that examine the differences in number of times characters choose each possible plan. For more information about my masters thesis, please look at my masters thesis page.

Behaviours of two sample characters according to the top-level choices they can make. This shows that two characters who started with the same template can learn differently and therefore choose to do different actions. Here, Anna chooses "Wait" most frequently, while Deb chooses "Move" most frequently.

Behaviours of two sample characters according to the top-level choices they can make with different starting personality templates. This example shows that the initial personality template does affect the choices that characters make.

Behaviours of a single character to show that it can learn specific goals such as "move towards a friend".

Characters learned based on their context. Context was based on a character's perceived achievement of their personal goals. In this image we are looking at the same character in two different contexts and can see that they prefer different actions/plans in different contexts. This difference was learnt automatically by the character and not pre-programmed.

While working for CSIRO, I used both the knowledge from my mechanical engineering degree, as well as from my undergraduate computer science degree. The work involved debugging a software program that determined air flow and temperatures in buildings using Newton-Raphson techniques. I was required to find the conditions under which the program failed and determine how to fix it. My research found and fixed many problems and was able to determine that the major problem was not a software problem, but a problem with the physics itself (the problem was mathematically unsolvable for certain input conditions).