You can just use Cockatrice for that. Sure it’s not as pretty or as easy, but it supports every card since you pretty much are playing paper magic and it’s not trying to be the referee.
I think a lot of people explicitly do not want to bother with playing essentially paper magic, because it requires quite a bit more concentration if your board state is complicated to not miss any triggers or phase change too far accidentally.
I’d say it goes beyond not being mutually exclusive. They complement each other, sometimes in surprising ways. Sacred geometry, concepts of frequency and vibrational rates, extracting signal from noise, if you are well versed in math and science you’ll find a lot of synchronicities. Fourier analysis dovetails with the concept of unity.
Pythagoras was what we might call an occultist. Newton was an alchemist (which isn’t about lead to gold, it’s about the transmutation of the Self), Jack Parsons was a Thelemite. Ramanujan credited his genius to visions.
Science and math can’t (yet) answer the big questions. There are things it doesn’t even try and touch. In my experience, curious minds are often interested in trying to attain a broader understanding of the universe and our place in it.
"Newton was an alchemist (which isn’t about lead to gold, it’s about the transmutation of the Self)"
Well, maybe not so much. That's kind of a 19th-20th century interpretation. We didn't want to believe that all these smart people really were into stupidity like turning lead into gold. Surely it must be much deeper than that! It must have been metaphors! But maybe not. Maybe they literally were into what they said they were into. It's not unlike how people want to claim that various religious stories weren't "really" about what they claim to be.
> We didn't want to believe that all these smart people really were into stupidity like turning lead into gold.
Alchemy was not stupid in the 17th century. You have the benefit of three centuries of subsequent scientific advances, to which geniuses like Isaac Newton, and those other smart people, contributed significantly.
Besides alchemy, Newton was deeply immersed in various occult studies. He was also a heretic, being a Unitarian, keeping his religious beliefs secret. Scientific research occupied only a part of his time. The seventeenth century was a time of religious and political turmoil, millenarianism and apocalyptic prophecy abounded. Newton was a man of his time.
Respectfully, Zosimus is one of the earliest Hellenistic writers on alchemy and he speaks of chemistry as a symbol:
“There are two sciences and two wisdoms, that of the Egyptians and that of the Hebrews, which latter is confirmed by divine justice. The science and wisdom of the most excellent dominate the one and the other. Both originate in olden times. Their origin is without a king, autonomous and immaterial; it is not concerned with material and corruptible bodies, it operates, without submitting to strange influences, supported by prayer and divine grace.
The symbol of chemistry is drawn from the creation by its adepts, who cleanse and save the divine soul bound in the elements, and who free the divine spirit from its mixture with the flesh.“
On the other hand we really can understand the chemistry that alchemists were fiddling with -- it wasn't metaphorical -- they really were messing around with chemicals and not souls. We still call some things by the names alchemists called them like "aqua regia" (literally "royal water") which is a nixture of nitric and hydrochloric acid that can dissolve gold and platinum. And which they hoped could therefore make more of it.
That to me is one of the most interesting aspects. Somehow, these people who were deeply spiritual, also were adepts of science, and while we can’t say any of them got it exactly right, the paths intersected enough that their contributions were in some ways foundational.
Psychology and psychiatry are two other fields that traveled the path of spirituality and occultism before becoming what we now term modern.
I am a consultant who developed the companion computer/autopilot and software environment for DRL drones used at the AIRR race sponsored by Lockheed in 2019. UZH was the team to beat and I met Davide and Elia there. They almost pulled it off but sports being what they are had a bit of a heartbreak at the end, and the team from Delft ended up pulling through and winning the $1mm prize. Delft then raced against Gab from DRL and iirc came behind by only 6 seconds.
So glad to see this team from UZH continued pushing the envelope and are now beating human champions. If you saw the team and what they managed in under a year, it was clear they were highly talented and human racers had their work cut out for them to stay ahead.
What is the general outline of going from a model of a craft (drone, sailboat, etc) to building a sim that can do reinforcement learning over a physical object interaction with its env?
I want to start playing with models, sims and collected data for sailboat racing- I know the RL/data science stuff, and I assume a good model of your craft takes time to build, and can be improved with collected data. What are some areas to explore when chaining model -> sim -> RL for performance?
I realize this is an extremely complex topic, with several PhDs worth of potential input- if you had to explain to someone technical what it looks like and where to keep digging, what would you say?
Models for drones are actually pretty simple. The races are indoors, so we can assume 0 wind. It’s really basic physics and aerodynamics. We had some sessions in a mocap lab where contestants were able to perform some flights and get some ground truth to tweak their sim -> actual drone dev loop. The simulator itself was based on the DRL simulator, but not the same version on the Steam store.
I did not develop the sim itself but did develop the hardware-in-the-loop portion of it along with things like real-time debugging, and output to the hitl. We had the sim rendering cameras which we output from the workstation to custom HDMI bridges over MIPI that we could treat as real cameras on the NVIDIA Xavier AGX. There was a data channel over Ethernet for IMU data.
I made a custom version of Eclipse that interfaced w GDB for debugging, which also was modified to stay in sync w the sim using PTP, w rewind capability.
As for sailboat modeling, yes it’s more complicated because of the effects of both wind and fluid dynamics. If I were approaching this, I’d probably try and find a physics simulator to start with. Getting ground truth will be difficult, but I imagine you would start w the IMU and GPS data off the boat, but having time synced ground truth for the waves and wind will probably be the hardest part.
Numerical simulation of aircraft is pretty straightforward. The hard part is going from the inertial frame into the aircraft's frame of reference, and back again. Once that part is down, the main procedure is to find the gravity vector in the body frame, calculate thrust, lift and drag vectors in the body frame, calculate any torques, sum everything, and then convert back into the inertial frame to do the numerical integration step. From memory, torques are the hardest part, since you need to work with either the time derivative of the quaternion, or the time derivative of the rotation matrix. But if you stick to standard coordinate frame conventions, it's just applying a formula.
The only difference between fixed wing and multirotors is the different models for forces in the body frame. A fixed wing aircraft would use an aerodynamic model of whatever complexity you like, and a model for the prop. A multirotor would use multiple prop models, and a drag model for the body. Most models for these things are pretty well defined, but you can choose just about anything that "fits" so long as you can justify it. And you can use the same basic setup for any aircraft (and indeed any robot) with a bit of forethought. The data part is mostly specifying things like, say, damping coefficients that you would then want to measure.
The dynamics are not the difficult part of simulating aircraft for RL, it's actually the rest of the environment. E.g. navigation tasks require you to build a navigable environment around your physics model, and specify things like reward functions.
I don't have any expertise in this field, but I expect sailboat training simulations would be much harder than aerial drones because of the underlying physics involved.
I'm sure flight simulations have to deal with some amount of fluid mechanics and turbulence to get an accurate simulation, but I suspect it's fairly simple and you can mostly model it accurately enough using Newtonian physics.
But for sailboats, the entire system relies profoundly on the interaction of two separate fluids with a single body and turbulence and viscosity are deeply interwined in making the boat go. Not to mention that the sail itself is a flexible deformable surface.
As a sailor, you're giving sailors a bit too much credit. Those things all matter, but to say that the average sail boat racer is even optimizing for all those things efficiently at once is a huge stretch. A lot of sail boat racing is strategy and properly performing the basically in a hostile environment. If you could ensure great strategy based on learned data, and immaculate execution based on properly tuned controls, I think you'd win easily.
I don't think GP is saying that sailors take all of those effects into account constantly, so much as he's saying a useful simulation would be monstrously difficult due to the underlying physics.
I've made robot models in the past, but never for anything involving water (although I actually have done physics simulations with water but nothing with robots). I don't know anything about sailing and I'm definitely not an expert at building simulations, but I can grok what GP meant and I agree with his assessment.
To give a rough analogy - it would be like trying to learn how to be a racecar driver on a videogame with simplified physics. There are professional drivers that use simulators and iRacing (or Assetto Corsa or a handful of other games) but none of them are training on Need for Speed, and it's because the difference is so stark you're actually handicapping yourself instead of learning how to drive. You need the simulation to be close enough to reality before it starts to become useful.
A simulation doesn’t necessarily need to be remotely physically accurate to be useful, as long as the simulated behaviour is qualitatively similar to the real thing. For sailing a small boat, I’d imagine the important things would be the shape of the sail and the heel of the boat for a given apparent wind, presented to whatever sensors your sailbot is using. For the water’s surface, random semi-regular perturbation (sum of sine waves) would be fine, and something similar (or maybe a random walk) for wind direction and strength.
For this kind of real-world robotics, you can’t optimise in any academic sense so you just have to go for effective and robust.
Well, for the drones, we did base things off ground truth captured in a mocap lab, and this helped the models significantly. There always will be a jump from simulation to real world, but the smaller you make that jump the quicker you’ll have a functioning vehicle. Without that, you can spend a ton of time (wasted) in simulation when the real world is substantially different. I’m sure a sum of sine waves would get you somewhere, but only so far. To me this is a difficult problem and I think it might be best to do most development in a real world environment.
I was just talking about sailboats specifically, where the external forces are highly unpredictable and similar in magnitude (albeit hopefully a fair bit smaller!) than your control authority over the boat.
The work you did on drones sounds very cool and in that scenario (high powered motors, crazy nonlinear dynamics, relatively small external perturbation, at least from how you described it?) I don't doubt that ground truthing your simulation using mocap data made a huge difference.
> as long as the simulated behaviour is qualitatively similar to the real thing.
My point is that I suspect that unless you have a very sophisticated simulation, it won't be.
> I’d imagine the important things would be the shape of the sail
The shape of a sail is itself a very complex thing to model and simulate. I'm not even a real sailor and I'm already thinking about camber, twist, and luffing. When sailing upwind, the sail is functioning like a wing using lift. When sailing downwind, it's relying on drag. Points in between use a mixture. This implies that turbulence and stall must be simulated at some level of fidelity.
If you've got a mainsail and a jib, then you have to worry about the slot effect and one sail blocking the wind of the other.
> and the heel of the boat for a given apparent wind
Not just heeling, but weather helm, leeway, drag, displacement, and how those interact.
Agree, I imagine just maxing VMG on the fly as conditions change is something a computer could already outperform humans easily.
I've wanted to make a simple sailing game for a while now but found it very hard to actually get something that feels right and compared to other activities there doesn't seem to be great resources on all the different parts of the physical system (in terms of Math).
> If you could ensure great strategy based on learned data
That's my point. If your learned data is coming from a simulation that doesn't model actual sailboat fluid dynamics, you've learned little.
A robot that learned to sail by studying a hollow cube floating in a bathtub full of marbles is not going to be able to make an actual sailboat do anything useful out on real water.
Yes getting timestamped and synchronized ground truth to build/verify your model will be quite challenging for something like this. For the drones we just took them to a mocap lab, and races are inside so we had the luxury of assuming 0 wind. The only remotely tricky part is handling ground effect from the props.
That's a very interest project. As a amateur sailor I have played with some models for sailing path optimizatio, wich can be somehow related to your problem. I started with a very simple model using sailing polar graphs, these map wind speed and course to maximum speed and usually based on empirical data, I found some DBs with this data, I can check if you are interest. Nevertheless for a better simulation you will at least need a simple model that gives you the forces at least especially if you want to simulate the boat acceleration, heeling and leeway. Simulating the sail foil behaviour would be very computational intesive as the airflow around it can get very complicated especially as the sail changes it's shape with it.
Reminds of me of my time 7 years back when i took the robotics courses from Davide. What a legendary professor alongwith Bernstein for AI, Sven for Computational-Econ and Boehlen for DBs.
It is, yes, but also this was done purely by VIO - courses were not mapped ahead of time. Contestants had very limited time on the actual drone, almost all their work had to be done via HITL simulation. The entire stack was done in maybe 6-8 months, then contestants produced their first code for the drone in a couple more months, and were flying shortly after. It was very clear that given more time, 6 seconds was going to be surpassed very quickly. All of this was live events too - contestants were tweaking code up until cameras rolled and spectators were in the stands.
It was mostly VIO. The drone had 4 cameras, two front facing, two aimed more at the sides. There were two IMUs on the companion computer (and more on the flight controller of course), as well as a downward facing rangefinder.
It was a software competition, whoever developed the best AI was the whole point. And we did NOT give them full course data ahead of time - they had to do this based off VIO only (visual inertial odometry).
Ha. I lived in Oxford for a year and the first day I arrived at my flat, there was a giant house spider. To this day it’s the biggest spider I’ve ever seen.
I’m with you. I drive a 24 year old 740iL. It’s a car, it functions well as one. If I want nav or whatever I have a cell phone after all. I even left the sound system original and listen to CDs. Its nice to just go back to basics for a change. I don’t feel like I’m missing anything by my car being dumb as a bag of rocks.
You see this a lot though. It’s because it becomes harder and harder to do something new and different when it’s all sort of been done before. Innovating something that’s been done to death is a lot harder than innovating when things are still less well defined.
I think video games are in this same space. Rarely does a game actually innovate or come up with something truly novel anymore. Ultima Online was the most amazing thing I ever saw at the time, but now that I’ve seen a million different MMOs the entire genre feels stale. Have fighting games really advanced much from either a Street Fighter type, Mortal Kombat, Marvel Vs Capcom or Smash Brothers style? What about action adventure - is God of War Ragnarok innovating anything? It doesn’t feel that different than playing any number of other games, just maybe more polished. Uncharted is just another take on Tomb Raider at the end of the day. Same thing with movies or television. There just isn’t that much new ground to break.
The actual rich are buying $1000 Gucci shoes that wear out just as fast as a $100 fashion sneaker these days. They put in a $100k kitchen and then do another full remodel in 10 years because it’s not the current style anymore. Cars? They lease or buy every 3 years perpetually so always have a car payment. I’m just not sure I buy this theory in the modern world. Everything we have is designed to last for a few years and then be replaced.
> $1000 Gucci shoes that wear out just as fast as a $100 fashion sneaker
Both are in a different league than really cheap shoes. I used to buy my shoes at Payless when I was younger, and they are literally made with paper, impossible to repair and destined to be trash within 3 months of daily use.
Shoes are an interesting case because they are destined to wear out with enough use, but high quality shoes wear out a lot slower and some kinds can be repaired or resoled, extending the life indefinitely.
I really can’t understand this perspective. Perhaps cheap gas is better than cheap electric cooktops. But my Miele which is radiant, not even induction, heats up VERY fast and provides a very predictable amount of heat via the digital interface. I cook a lot, and thought I’d miss gas when buying my new house, but just about the only change I needed was to get a flat bottomed wok. Electric can definitely be more than adequate on the high end, imo.
I launched my own matrix server for my company two years ago and I’ve never had to do a thing with it. It gets frequent use by ~10 people, so not huge, but it’s been quite easy to deploy and maintain.
Not sure about the rest of the state but definitely no basements here in South Florida. I haven’t even seen any houses w a crawl space when I was moving here. Pretty much just concrete block construction on slab. Can’t really dig far on a swamp…
I guess you guys have some firmer land up there. Here if it isn't pure swamp, its limestone which water has no problem passing through, hence no basements in most locations.
