
Three States and a Plan: The A.I. of F.E.A.R (2006) [pdf] - Wlad007
http://alumni.media.mit.edu/~jorkin/gdc2006_orkin_jeff_fear.pdf
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oolongCat
Ahh GOAP This is a very interesting approach to AI. This topic was a huge part
of my FYP. I got this to work on a GPU with cuda.

Anyways,
[http://alumni.media.mit.edu/~jorkin/goap.html](http://alumni.media.mit.edu/~jorkin/goap.html)
(more from the same author : Jeff Orkin)

has a lot more information about this approach.

[https://github.com/stolk/GPGOAP](https://github.com/stolk/GPGOAP) (not mine)
for anyone who wants to look at this in action (c/c++ code).

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jeremiep
The AI of Quake3 is also a great read!

[http://fd.fabiensanglard.net/quake3/The-Quake-III-Arena-
Bot....](http://fd.fabiensanglard.net/quake3/The-Quake-III-Arena-Bot.pdf)

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danielmorozoff
I would be interested in knowing how does constraining state complexity in AI
get handled when designing games that must meet certain framerate and
performance reqs- especially in FPS games? Are there instances where decisions
are forced because of the need for an agent to undertake an action? And what
heuristics are used? This is definitely part of chess/ board game playing AIs
with time restrictions.

Has any work been done in trying to model AI as a deep learning problem,
getting testers to play against one another and running feature extractors on
their behaviors (a la deep mind) and training NN models on this data?

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Natanael_L
Google's Go playing AI which recently beat some world champions? Sounds just
like what you describe.

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danielmorozoff
As I described in my question- board games ai aka go this has been done for
years. I'm interested in fps games

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Illniyar
I've read about half the article so far, but isnt this basically prolog?

Is there reference to efficency in the document? Constraint solvers like
prolog are pretty slow.

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qbrass
They added a cost per action and use A* for graph traversal instead of
Prolog's depth-first search.

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eggy
I am not a gamer, but I did know of F.E.A.R.

The paper is from 2006? Are these still valid techniques, or have they been
supplanted with evolving A.I.?

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Merad
> have they been supplanted with evolving A.I.?

Not to my knowledge. In fact, the AI of F.E.A.R. is still more or less looked
at as a benchmark of good FPS AI. I'm really struggling to think of any game
that has surpassed it. The FPS genre has been dominated by titles focused on
multiplayer for the last 6-8 years, so AI has been fairly stagnant.

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corysama
In games, AI is not my area. But, what I've seen is that games try to avoid
training-based AI because it is difficult to get predictable, controllable
results. Training an neural/genetic/whatever system is great until a designer
asks you to code in a few exceptional situations and a few extra guarantees.
However, there is apparently some movement into that area going on.

Here's a recent vid about game AI.
[https://www.youtube.com/watch?v=jse_ZleruJU&t=11m44s](https://www.youtube.com/watch?v=jse_ZleruJU&t=11m44s)
It talks about the progression from FSMs, to Behavior Trees, to Utility AI,
into Neural Nets and eventually Neural Evolution.

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vsviridov
F.E.A.R. is one of my favourite games, and the AI was really well done.

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saintwind
Agreed. Great story too, for an FPS. Shame the sequels were rather lackluster.

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protoster
HE'S TOO FAST

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saintwind
SQUAD, CHECK IN!

