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21st Century AI

A blog about achieving meaningful Artificial Intelligence

Posts Tagged ‘Bad Game AI’

Bad Game AI / Good Game AI (Part 2)

Thursday, June 16th, 2011

So, we left the last post with the intention of finding other games that had good AI, or at least AI that didn’t suck. We’ve asked everybody we know, we scoured our game collection and we’ve still come up empty. You know what? Almost all game AI sucks; some just suck more than others.

Without naming names – but getting as close as we dare – here are some real stinkers:

Sports Games. I like sports games; especially ‘management’ sports games where you get to trade for players and call the plays. I’m not interested in actually being the quarterback or the batter and precisely timing when you press the ‘A’ button or whatever. I like sports games because the AI sucks and I can easily manage the Chicago Cubs to win back to back to back World Series championships (for my foreign readers the Chicago Cubs are the worst team in the history of professional baseball or maybe professional sports in general and, yes, I’m a Cubs fan).

To me, this especially galling because writing sports AI should be pretty easy; well, easier than writing wargame AI. First, baseball and football (the only sports that really excite me from a game AI perspective) are really well understood and there is a ton of statistics recorded since the beginning of these sports. Stats are very important in creating good AI. It allows us to create accurate models of what has happened and what will probably happen in the future. We can use this to our advantage.

A quick example: you’re calling the defensive plays in a football game. It is third down and the offense has to move the ball 25 yards for a first down. What do you think is going to happen? Well, most humans would know that the offense is going to call a passing play. What should the defense do? I’ll give you a hint: don’t expect a running play off tackle. Yet, most football games are pretty clueless in this classic ‘passing down’ situation. Indeed, sports games AI is clueless when it comes to knowing what happened in the past and what is likely to occur next. They don’t keep any stats for AI. Doing so would come in handy for unsupervised machine learning (I was going to link to a post below but, hey, just scroll down); a subject I plan on writing about a great deal more in the future.

And one more thing about sports games: they have no concept of what constitutes a good trade or a bad trade. Let’s say you want to trade for Babe Ruth (for our foreign readers: arguably the greatest baseball player of all time). At some level, the game has a ‘value’ associated with the ‘Babe Ruth’ data object. It could be a letter value, like ‘A’, or it could be a numerical value like 97. If you offer the AI a trade of ten worthless players, valued in the 10-20 range (or ‘D’ players) the AI will take the trade because it is getting more ‘value’ (100-200 ‘player points’ for 97 ‘player points) even though it’s a stupid decision. Yes, I know some games only allow you make three or four player trades, but the basic principle is the same: sport game AI usually makes bad trades. And the reason for this is that the AI is ‘rule based’ or ‘case based reasoning’. Again, I promise I’ll write more about this type of AI in the future, but for now just be aware that this type of AI sucks.

Real Time Strategy (RTS) Games (Wargames with Tech Trees). There are a lot of games that fall into this category and they all have serious AI problems. First, writing AI for wargames is very difficult (I do for a living, so, yeah, I am an expert on this). Second, RTS games can’t ‘afford’ to spend many clock cycles on AI because they have lots of animation going on the screen, polling for user input, etc. and this results in very shallow AI decisions. Lastly, the addition of a Tech Tree (should the AI ‘research’ longitude or crop rotation?) doesn’t make the AI decisions any easier.

If anybody out there knows of a RTS game where the AI doesn’t suck, please drop me a line. I would love to play it.

This, unfortunately, brings us to:

Civilization V. Well, so much for not using names. I haven’t even played this game but I just read this review on I Heart Chaos: “Speaking of “miscalculating”, (a polite word for “cheating”) there is a serious issue with Civilization V’s artificial intelligence. It is so

unbelievably unbalanced that the experience suffers for it.” (http://www.iheartchaos.com/post/6492357569/ihc-video-game-reviews-civilization-v).

CES 1989

(L to R) The game designer of the Civilization game series, the author of this blog and Johnny Wilson (game magazine writer) at the 1989 CES show. Couple of interesting observations: I had the #1 game at the time and we all (except Johnny Wilson) had more hair.

Well that sounds kinda mean-spirited of me, doesn’t it? I haven’t even played the game, but here I’m citing another review that says Civ 5 has lousy AI. Well, the problem is that whole Civ series (and I have played some of the earlier ones) all suffered from bad AI, or AI that just plain cheated. And that’s another problem; the game developer (who shall remain nameless) kinda has a history of using ‘cheating’ AI. That is to say, his AI often ‘sees through’ the fog of war (i.e. you, the player, can’t see your opponent’s units but your computer opponent can see all of yours), and, well, there’s just not a nice way to say this… the ‘dice rolls’ have a tendency to get fudged… in the favor of the computer.

So, there you have it: the current state of AI for computer games isn’t pretty. For the most part, it’s ‘rule based’ or ‘case based reasoning’ which is extremely inflexible (we sometimes use the phrase ‘brittle’ to indicate AI that is easily broken.

I am more convinced than ever that the solution is unsupervised machine learning. So, I will be returning to that topic in the next blog entry.

 

 

Bad Game AI / Good Game AI (Part 1)

Thursday, June 9th, 2011

Most game AI is bad AI. Let’s be honest; it’s not just bad, it sucks.

I’ve been writing and playing computer games since the early 1980s and I haven’t seen even a modest improvement in the quality of computer opponents. There are a few notable exceptions – and we’ll get to them shortly – but, the vast majority of commercial games that are released were developed with little thought, or budget, given to AI.

So, since it’s such a short list, let’s start with a few computer games that have good AI:

Computer Chess. Any computer chess program that is available today, including ‘freebie’ online Java applets will kick your ass. Back in the ‘70s I had an ‘electronic chess game’ that played as well as I did (I was about a 1600 level player at the time). The game had various levels of AI; but all that changed was how much time the machine was given to make a move. If you put it on the top level it would take forever contemplating the all the responses to the opening P-K4.

So, why was chess AI pretty good thirty-five years ago and even better now? There are a couple of reasons, the first being that chess can be divided into three ‘phases’: the opening, the middle and the endgame. Chess openings are very well understood and there are number of ‘standard’ texts on the subject such as Batsford Chess Openings Volume 1 and 2. These chess openings are available in various file formats and are easily integrated into a chess engine. So, until the program is ‘out of book’ the most important moves, the opening moves, are expertly played by the program without any AI at all. There are also books for endgame positions. So, really, the only difficult area for chess programs is the middlegame.

1st Chess problem solved by computer

1st Chess problem solved by computer by Dr. Dietrich Prinz with the Manchester Mark 1 in 1951 (White to mate in two. The solution is: R - R6, PxR. P - N7 Mate.)

There are dozens of very good articles, papers and books on evaluating chess positions using heuristic evaluation function. Here’s a pretty good page on the subject, even though it looks like all the picture links are broken: http://www.cs.cornell.edu/boom/2004sp/ProjectArch/Chess/algorithms.html ). And here’s a link to a series on building a chess engine: http://www.gamedev.net/page/resources/_/reference/programming/artificial-intelligence/gaming/c

hess-programming-part-vi-evaluation-functions-r1208 .

Chess was one of the first games to be implemented on computers. The first chess problem solved by a computer see picture) was done by Dr. Dietrich Prinz with the Manchester Mark 1 in 1951 (see picture, right).

Though I could be wrong, I think Dr. Prinz’s program simply employed brute force to solve the problem.

So, why is it comparatively easy to find/write good chess AI? Opening and endgame databases are readily available, evaluation functions for board positions are well understood and (I suspect I’ll get some flak for saying this) it’s a relatively easy game (at least to program, not to master). Also, there are not a lot of pieces, their moves are restricted, the rules of the game are simple and the board size is fixed.

Chris Crawford’s Patton vs. Rommel. Crawford’s Patton vs. Rommel was a wargame that came out in 1987. On the PC (remember this was before Windows) it ran in 640kb (and that included the operating system). The display was 640 x 200 x 2, if I remember correctly (see screen shot).

Chris Crawford's Patton vs. Rommel

Chris Crawford's Patton vs. Rommel (1987)

I haven’t played the game in over 20 years, but I remember being very impressed by the AI, specifically how the program had a ‘feel’ for the tactical situation. A very important part of the game was the ‘road net’. Units moved much faster on roads and it was easy to get your units caught up in traffic jams. When that happened the AI would warn the user. This really shocked me when I first played the game. Chris employed what he called ‘geometric AI’ in Patton vs. Rommel. He goes into more details in his book, “Chris Crawford on Game Design,” (http://www.amazon.com/Chris-Crawford-Game-Design/dp/0131460994).

 

There are plenty of great games out there, but that’s not what this post is about. The question is what games have good AI? I’m going to need to think about this and see if I can add some more titles to the ‘good AI’ list, because I sure have a ton for the ‘bad AI’ list.