Clojure Plays Mario
blog.phronemophobic.com
Clojure Plays Mario
1–10 of 43 posts
Re: Clojure Plays Mario
#2I can never look at Mario the same
Re: Clojure Plays Mario
#3This is really cool. I hadn't thought of a path-finding algorithm working on something like a Mario run. Nice to see AI approaches like this aren't getting forgotten for all the neural nets and machine learning.
Re: Clojure Plays Mario
#4Y'know, the thing I least like about these AI video game players is how unlike humans they look. I was wondering about the difference, and I think it comes down to two parts. First and foremost, human players generally prefer routes with a lot of tolerance for input error. Second, humans take frequently "mental planning breaks," stopping for a moment in safe spots before challenging areas.
I think you could juggle the heuristics to demonstrate the preference for input error. For ML training, you could just random vary input timing by up to 20ms or so to teach the algorithm to favor safer moves. For path finding, it's trickier, but there's probably a way to favor "wide" paths. I'm less sure how to express the second concept, pausing briefly in "safe areas," but I imagine it's maybe noticing a place where significant amounts of entering no inputs does not affect the results.
Re: Clojure Plays Mario
#5This is really cool. I hadn't thought of a path-finding algorithm working on something like a Mario run. Nice to see AI approaches like this aren't getting forgotten for all the neural nets and machine learning.
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Re: Clojure Plays Mario
#6Y'know, the thing I least like about these AI video game players is how unlike humans they look. I was wondering about the difference, and I think it comes down to two parts. First and foremost, human players generally prefer routes with a lot of tolerance for input error. Second, humans take frequently "mental planning breaks," stopping for a moment in safe spots before challenging areas. I think you could juggle th…
I don't think making humans comfortable is the goal with respect to AI. The goal is to actually solve a problem. Performance is second. Human comfort is a distant third or beyond.
When AI can reliably solve a problem without significant negative consequenses from time to time, it's a win. How humans feel about the method is effectively irrelevant.
Re: Clojure Plays Mario
#7emulator integration is https://www.libretro.com/index.php/api/?amp=1 (warning, f’ed website) and the clojure wrapper (by OP) is: https://github.com/phronmophobic/clj-libretro/blob/67f186e87...
really cool!
Re: Clojure Plays Mario
#8Y'know, the thing I least like about these AI video game players is how unlike humans they look. I was wondering about the difference, and I think it comes down to two parts. First and foremost, human players generally prefer routes with a lot of tolerance for input error. Second, humans take frequently "mental planning breaks," stopping for a moment in safe spots before challenging areas. I think you could juggle th…
I just couldn't bear all that walking and jumping into near misses in the video.
Re: Clojure Plays Mario
#9Y'know, the thing I least like about these AI video game players is how unlike humans they look. I was wondering about the difference, and I think it comes down to two parts. First and foremost, human players generally prefer routes with a lot of tolerance for input error. Second, humans take frequently "mental planning breaks," stopping for a moment in safe spots before challenging areas. I think you could juggle th…
I don't think making humans comfortable is the goal with respect to AI. The goal is to actually solve a problem. Performance is second. Human comfort is a distant third or beyond. When AI can reliably solve a problem without significant negative consequenses from time to time, it's a win. How humans feel about the method is effectively irrelevant.
> I don't think making humans comfortable is the goal with respect to AI
According to whom?
AI in games, has historically been all about human comfort/enjoyment. Extremely good AI that seems "unnatural" to humans is usually not the goal.
Re: Clojure Plays Mario
#10Y'know, the thing I least like about these AI video game players is how unlike humans they look. I was wondering about the difference, and I think it comes down to two parts. First and foremost, human players generally prefer routes with a lot of tolerance for input error. Second, humans take frequently "mental planning breaks," stopping for a moment in safe spots before challenging areas. I think you could juggle th…
What you’re basically describing is bounded rationality, which has been widely studied in behavioral economics, psychology, and engineering applications (Simon and Gigerenzer are two big names to google). A common framework for formalizing it is as what boils down versions of rate-distortion problems from information theory (very related to Bayesian statistics).
The reason it’s of engineering interest is, like you observe, bounded-rationality gives you solutions that are sub-optimal but more robust and often simpler.
Moreover, finding wide path solutions emerges naturally from sampling-based motion planners. These planners are asymptotically optimal, but if you terminate them early, they are more likely to give you a solution that goes through large gaps, not smaller ones, because it’s unlikely to sample a trajectory that goes through a tight space without heavy sampling. You could probably formulate that in the rate-distortion framework but I haven’t thought about how to do it precisely.