hsm
napkinXC
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hsm
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Is it ok to have state-wide conditions in a Finite State Machine? Or does that defeat the purpose?
Finally you can make a more complete Hierarchical (or Nested) State Machine, which allows you to have states within states. This is what we've done in several games I've worked on. This can allow reusing states in multiple contexts, such as being in an Idle state that pushes a Targeting state, or in a Running state that also pushes the Targeting state. You are then considered in all of the states on your state stack. This is tricky to implement right though and needs careful design, but used correctly can be extremely powerful. I'm aware of a C++ HSM library that I can recommend ( https://github.com/amaiorano/hsm ), but there's probably other good ones out there.
napkinXC
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Predicting numerical values to a very high accuracy
If you only have 198 possible values then extreme multiclass models might benefit here with better precision and faster convergence. For example probabilistic label trees might have some relevance. Vowpal Wabbit also has specific reductions for extreme multi class problems. Might be worth a try if other alternatives still don't work out.
What are some alternatives?
sml - C++14 State Machine library
ehsm - An End-to-End Distributed and Scalable Cloud KMS (Key Management System) built on top of Intel SGX enclave-based HSM (Hardware Security Module), aka eHSM.
vowpal_wabbit - Vowpal Wabbit is a machine learning system which pushes the frontier of machine learning with techniques such as online, hashing, allreduce, reductions, learning2search, active, and interactive learning.
HFSM2 - High-Performance Hierarchical Finite State Machine Framework
tensorflow - An Open Source Machine Learning Framework for Everyone
lizardfs - LizardFS is an Open Source Distributed File System licensed under GPLv3.
PaddlePaddle - PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice （『飞桨』核心框架，深度学习&机器学习高性能单机、分布式训练和跨平台部署）
hsmcpp - C++ based Hierarchical / Finite State Machine library oriented for embedded and RTOS systems.
CNTK - Microsoft Cognitive Toolkit (CNTK), an open source deep-learning toolkit
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration
Three-Filters-to-Normal - Three-Filters-to-Normal: An Accurate and Ultrafast Surface Normal Estimator (RAL+ICRA'21)