rlcard VS Bullet

Hi. I’ve decided to do a project to adapt an rl library to support self-play. This is a project so I can teach myself more about building rl systems. I’ve been considering working with the environment system from rlcard https://github.com/datamllab/rlcard/ but wonder if there are other more widely-used self play environment libraries. Thanks.

Can you point me to some active forums for poker bot building? I can only find github repo like https://github.com/datamllab/rlcard, which is mostly reinforcement learning. Whereas SoTA approach like Pluribus is more about game theory.

Build a Poker bot with RLCard

Probably the easiest way for you to get started is to implement your game on an open source RL framework that has working implementations of some basic CFR variations as well as some other self-play algorithms such as NFSP. OpenSpiel and RLCard are two that I am aware of. Depending on the complexity of your game and how strong your agent needs to play, you might be satisfied with the performance you get using by one of these frameworks.

For typical game physics engines... not that much. Math libraries like Eigen or Blaze use lots of template metaprogramming techniques under the hood that can help when you're doing large batched matrix multiplications (since it can remove temporary allocations at compile-time and can also fuse operations efficiently, as well as applying various SIMD optimizations), but it doesn't really help when you need lots of small operations (with mat3 / mat4 / vec3 / quat / etc.). Typical game physics engines tend to use iterative algorithms for their solvers (Gauss-Seidel, PBD, etc...) instead of batched "matrix"-oriented ones, so you'll get less benefits out of Eigen / Blaze compared to what you typically see in deep learning / scientific computing workloads.

The codebases I've seen in many game physics engines seem to all roll their own math libraries for these stuff, or even just use SIMD (SSE / AVX) intrinsics directly. Examples: PhysX (https://github.com/NVIDIA-Omniverse/PhysX), Box2D (https://github.com/erincatto/box2d), Bullet (https://github.com/bulletphysics/bullet3)...

I suspect most C++ physics libraries like Box2D (https://github.com/erincatto/box2d) or Bullet3 (https://github.com/bulletphysics/bullet3) could really benefit a lot from SIMD.

No, they replaced Bullet with Jolt. That is considerably more than "some adjustment", regardless of what you think of the result.

Vulkan graphics via Intel GVK, and physics via Bullet

The first two have a bunch of great examples, and I’m tying them together by refactoring some of the THREE examples to fit the ECS paradigm defined in AFrame. then upping the ante by adding physics using AMMO, which is more challenging since it’s only a partial implementation of Bullet, and already poorly documented (yet popular) physics engine.

Plus, SM uses a system called bullet physics, I imagine this would be rather complex to rework into a modern engine such as Unreal or Unity (after all, the majority of performance issues come from the physics engine rather than the graphics engine)

The physics in HDT-SMP are actually being calculated outside of Skyrim's engine with Bullet, an open-source physics engine. So this isn't some limitation of Skyrim's engine.