For AI researcher Game AI is like porn. It's cheap tricks and obviously fake but oddly fascinating. Sometimes you find a new trick you want to try in real life.
Marvin Minsky once said "I bet the human brain is a kludge." If I had to bet, I would say that human brain is full of dirty tricks, incomplete solutions, shortcuts and artificially limited problem spaces evolved to pick berries and avoid tigers, not to understand the world. Combining many tricks together can create illusion of generality that is very convincing.
> If I had to bet, I would say that human brain is full of dirty tricks, incomplete solutions, shortcuts and artificially limited problem spaces evolved to pick berries and avoid tigers, not to understand the world.
Wikipedia has an interesting list of cognitive biases [1]. Going through these, I tend to think of all of them as heuristic failures, where those shortcuts and incomplete solutions are pushed to edge cases.
Yeah, that's the thing - the brain and body evolved for a much different environment than the one we find ourselves in today.
So some aspects which used to be advantages are now disadvantages that we have to actively manage with things like exercise, healthy diet, meditation. Which the brain fights against.
I’d take the other side of that strongly, if it was possible. The human brain is definitely not a kludge by any definition. And a lot of the tricks people think they know are not tricks at all.
Neuroscientists are the new doctors of the 50s. We thought the appendix was useless turns out it has many uses. We thought priming and all these “tricks” were things and then the crisis and Kahneman et al were debunked.
I bet the brain is just as elegant and powerful as it has to be to do the incredible complex things we do, and we’re just so far from really understanding it that we run around appendicizing all sorts of things we just don’t really know well yet.
The kludginess of brains is textbook neuroscience, from instincts to reflexes, to illusions and more.
Indeed, Game AI puts the "Game" first -- as it should for Games, but to the detriment of anyone who cares more about AI and wants Games to be a fun place to study AI.
If we split Game AI into "problem solving" (like pathfinding) and "opponent personality", then we can recover a lot of good AI that generalizes beyond games, without being misled by the parts that only useful for tricking people in a toy environment.
Very cool. I always expect a link like this to either be some super basic examples (e.g. how to implement flocking) or articles detailing techniques used in games from ~20 years ago.
Very cool how recent and modern these are (along with super reputable authors)
Is this directly from the authors? If yes, I'm a bit shocked given the prices for the book when searching for ed 1, ed 2 and ed 3 on Google. Please add a donation button to the site.
I just finished the first four sections and I love it. Thanks a lot!
They always do this when the next version of the book is close to coming out. The first 2 have been available for free for a while. It is expected with this that the 4th is coming soon.
I've been thinking a lot about trying to make an AI for a turn based 4X game. I believe an AI that could defeat the strongest human players in (for example) Civilization would be more impressive than AlphaStar and the Dota AIs.
I think it might give the gaming industry a kick in the pants to start utilizing more advance AI techniques in general, since it seems almost all discussions of strong AI in games are dominated by apologists explaining why it's not practical. Just one example of strong AI in a successful game would change the industry.
After strong AIs are common, we can persue the even more interesting task of dumbing them down in fun ways.
Having an AI defeat the strongest human players (without cheating) isn't often the hard part, its making it fun, believable, interesting or, indeed, beatable (its no fun if you can never ever win) is often the hard part. A perfectly minmaxing AI that makes perfect decisions isn't very interesting to players. Outsmarting players in interesting ways is, well, interesting, but just always playing the best move in any given scenario (like what deep blue did with its search-based "AI") can create perfect play if the search space is within the bounds of time/memory of the AI, but that's not very interesting to play against or watch.
> Unfortunately, the time between seeing a decision acted out and the actual act of making that decision can mean that all relevant information has already been discarded. Ideally if the entire game simu-lation could be rewound to the exact moment in time when the error occurred, it would make notoriously difficult problems to debug, trivial to understand why they occurred.
> Game engines have typically made reproducing these types of problems easier using deterministic playback methods (Dickinson 2001), where the entire state of the game simu-lation can jump back in time and resimulate the same problem over and over (Llopis 2008).
Imagine if you could do this for all programming? [from chapter 6]
The RVO chapter, and that concept I general is an amazing one because they really created a method for 2 autonomous characters avoiding collisions on a natural way - with code that is easy to understand
MAXPOOL|6 years ago
For AI researcher Game AI is like porn. It's cheap tricks and obviously fake but oddly fascinating. Sometimes you find a new trick you want to try in real life.
Marvin Minsky once said "I bet the human brain is a kludge." If I had to bet, I would say that human brain is full of dirty tricks, incomplete solutions, shortcuts and artificially limited problem spaces evolved to pick berries and avoid tigers, not to understand the world. Combining many tricks together can create illusion of generality that is very convincing.
MereInterest|6 years ago
Wikipedia has an interesting list of cognitive biases [1]. Going through these, I tend to think of all of them as heuristic failures, where those shortcuts and incomplete solutions are pushed to edge cases.
[1] https://en.wikipedia.org/wiki/List_of_cognitive_biases
Reedx|6 years ago
Yeah, that's the thing - the brain and body evolved for a much different environment than the one we find ourselves in today.
So some aspects which used to be advantages are now disadvantages that we have to actively manage with things like exercise, healthy diet, meditation. Which the brain fights against.
nwienert|6 years ago
Neuroscientists are the new doctors of the 50s. We thought the appendix was useless turns out it has many uses. We thought priming and all these “tricks” were things and then the crisis and Kahneman et al were debunked.
I bet the brain is just as elegant and powerful as it has to be to do the incredible complex things we do, and we’re just so far from really understanding it that we run around appendicizing all sorts of things we just don’t really know well yet.
lonelappde|6 years ago
Indeed, Game AI puts the "Game" first -- as it should for Games, but to the detriment of anyone who cares more about AI and wants Games to be a fun place to study AI.
If we split Game AI into "problem solving" (like pathfinding) and "opponent personality", then we can recover a lot of good AI that generalizes beyond games, without being misled by the parts that only useful for tricking people in a toy environment.
echelon|6 years ago
Can we still cite Marvin Minsky in the AI field given the allegations that have arisen regarding his relationship with Epstein and sex trafficking?
We should find better luminaries.
I'm all for redemption and I hope Stallman comes around and apologizes, but Minsky went to the grave with whatever happened.
fxtentacle|6 years ago
And even though they gave a talk about in in 2015, their "Simplest AI Trick in the Book" is still not implemented by some games released nowadays.
In case you don't know it, it's:
0.2s reaction time for aiming
+ 0.4s reaction time for yes/no decisions
+ additional delay for ambiguity, surprise, or limited visibility
I wholeheartedly agree with this advice. Just seeing your opponent taking a moment to think makes whatever it is they do so much more convincing.
thebrain|6 years ago
wget -r -A.pdf http://www.gameaipro.com/
wget -r -A.zip http://www.gameaipro.com/
fxtentacle|6 years ago
a) sell PDF ebooks
and
b) explicitly say that you are not supposed to re-upload the content elsewhere.
bdickason|6 years ago
Very cool how recent and modern these are (along with super reputable authors)
KenanSulayman|6 years ago
I just finished the first four sections and I love it. Thanks a lot!
runevault|6 years ago
Buttons840|6 years ago
I think it might give the gaming industry a kick in the pants to start utilizing more advance AI techniques in general, since it seems almost all discussions of strong AI in games are dominated by apologists explaining why it's not practical. Just one example of strong AI in a successful game would change the industry.
After strong AIs are common, we can persue the even more interesting task of dumbing them down in fun ways.
dkersten|6 years ago
Namrog84|6 years ago
An artificially handicapped or limited smart ai in video games is often obvious and not fun.
spmealin|6 years ago
bmn__|6 years ago
dmix|6 years ago
> Game engines have typically made reproducing these types of problems easier using deterministic playback methods (Dickinson 2001), where the entire state of the game simu-lation can jump back in time and resimulate the same problem over and over (Llopis 2008).
Imagine if you could do this for all programming? [from chapter 6]
anarazel|6 years ago
rr comes pretty close. https://rr-project.org/
syspec|6 years ago
hesdeadjim|6 years ago
SergeAx|6 years ago
SloopJon|6 years ago
coder1001|6 years ago
mottosso|6 years ago
unknown|6 years ago
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Jahak|6 years ago
m3kw9|6 years ago
The_mboga_real|6 years ago
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