Computing Your Skill. Summary I describe how the True. Skill algorithm works using concepts youre already familiar with. True. Skill is used on Xbox Live to rank and match players and it serves as a great way to understand how statistical machine learning is actually applied today. Ive also created an open source project where I implemented True. Skill three different times in increasing complexity and capability. In addition, Ive created a detailed supplemental math paper that works out equations that I gloss over here. Feel free to jump to sections that look interesting and ignore ones that seem boring. Dont worry if this post seems a bit long, there are lots of pictures. Introduction. It seemed easy enough I wanted to create a database to track the skill levels of my coworkers in chess and foosball. I already knew that I wasnt very good at foosball and would bring down better players. I was curious if an algorithm could do a better job at creating well balanced matches. Part I of Alan Turing, Father of the Modern Computer provides an overview of Turings many major contributions to the development of the computer and. Virus In My Computer Clean My Computer Fix, Clean VIRUS IN MY COMPUTER CLEAN MY COMPUTER And Optimize PC SPEED Up Your PC FREE Scan Now Computing Your Skill. Mar 18, 2010. Summary I describe how the TrueSkill algorithm works using concepts youre already familiar with. TrueSkill is used on Xbox. I also wanted to see if I was improving at chess. I knew I needed to have an easy way to collect results from everyone and then use an algorithm that would keep getting better with moredata. I was looking for a way to compress all that data and distill it down to some simple knowledge of how skilled people are. Based on some previousthings that I had heard about, this seemed like a good fit for machine learning. But, theres a problem. Machine learning is a hot area in Computer Science but its intimidating. Like most subjects, theres a lotto learn to be an expert in the field. I didnt need to go very deep I just needed to understand enough to solve my problem. Computer Chess Ware' title='Computer Chess Ware' />I found a link to the paper describing the True. Skill algorithm and I read it several times, but it didnt make sense. Computer Chess Ware' title='Computer Chess Ware' />It was only 8 pages long, but it seemed beyond my capability to understand. I felt dumb. Even so, I was too stubborn to give up. Jamie Zawinski said it well Not knowing something doesnt mean youre dumb it just means you dont know it. I learned that the problem isnt the difficulty of the ideas themselves, but rather that the ideas make too big of a jump from the math that we typically learnin school. This is sad because underneath the apparent complexity lies some beautiful concepts. In hindsight, the algorithm seems relatively simple, but it took me several months to arrive at that conclusion. My hope is that I can short circuit the haphazard and slow process I went through and take you directly to the beauty of understanding whats inside the gem that is the True. Skill algorithm. Skill Probability of Winning. Skill is tricky to measure. Being good at something takes deliberate practice and sometimes a bit of luck. How do you measure that in a personYou could just ask someone if theyre skilled, but this would only give a rough approximation since people tend to be overconfident in their ability. Perhaps a better question is what would the units of skill be For something like the 1. However, for a game like chess, its harder because all thats really important is if you win, lose, or draw. It might make sense to just tally the total number of wins and losses, but this wouldnt be fair to people that played a lot or a little. Slightly better is to record the percent of games that you win. However, this wouldnt be fair to people that beat up on far worse players or players who got decimated but maybe learned a thing or two. The goal of most games is to win, but if you win too much, then youre probably not challenging yourself. Ideally, if all players won about half of their games, wed say things are balanced. In this ideal scenario, everyone would have a near 5. Finding universal units of skill is too hard, so well just give up and not use any units. The only thing we really care about is roughly whos better than whom and by how much. One way of doing this is coming up with a scale where each person has a unit less number expressing their rating that you could use for comparison. If a player has a skill rating much higher than someone else, wed expect them to win if they played each other. The key idea is that a single skill number is meaningless. Whats important is how that number compares with others. This is an important point worth repeating skill only makes sense if its relative to something else. Wed like to come up with a system that gives us numbers that are useful for comparing a persons skill. In particular, wed like to have a skill rating system that we could use to predict the probability of winning, losing, or drawing in matches based on a numerical rating. Well spend the rest of our time coming up with a system to calculate and update these skill numbers with the assumption that they can be used to determine the probability of an outcome. What Exactly is Probability AnywayYou can learn about probability if youre willing to flip a coin a lot. You flip a few times Heads, heads, tails Each flip has a seemingly random outcome. However, random usually means that you havent looked long enough to see a pattern emerge. If we take the total number of heads and divide it by the total number of flips, we see a very definite pattern emerge But you knew that it was going to be a 5. When saying something is random, we often mean its bounded within some range. It turns out that a better metaphor is to think of a bullseye that archers shoot at. Each arrow will land somewhere near that center. It would be extraordinary to see an arrow hit the bullseye exactly. Most of the arrows will seem to be randomly scattered around it. Although random, its far more likely that arrows will be near the target than, for example, way out in the woods well, except if I was the archer. This isnt a new metaphor the Greek word stochos refers to a stick set up to aim at. Its where statisticians get the word stochastic a fancy, but slightly more correct word than random. The distribution of arrows brings up another key point All things are possible, but not all things are probable. Probability has changed how ordinary people think, a feat that rarely happens in mathematics. The very idea that you could understand anything about future outcomes is such a big leap in thought that it baffled Blaise Pascal, one of the best mathematicians in history. In the summer of 1. Pascal exchanged a series of letters with Pierre de Fermat, another brilliant mathematician, concerning an unfinished game. Pascal wanted to know how to divide money among gamblers if they have to leave before the game is finished. Splitting the money fairly required some notion of the probability of outcomes if the game would have been played until the end. This problem gave birth to the field of probability and laid the foundation for lots of fun things like life insurance, casino games, and scary financial derivatives. But probability is more general than predicting the future its a measure of your ignorance of something. It doesnt matter if the event is set to happen in the future or if it happened months ago. All that matters is that you lack knowledge in something. Just because we lack knowledge doesnt mean we cant do anything useful, but well have to do a lot more coin flips to see it. Aggregating Observations. The real magic happens when we aggregate a lot of observations. What would happen if you flipped a coin 1. Lots of things are possible, but in my case I got 5. Lego Star Wars 2 Ps2 Iso Espanol. Thats about half, so its not surprising.