Does a given model converge after Gaussian blurring? What does it do in the presence of noise, given the curse of dimensionality? OpenCog integrates PLN and MO

Does a given model converge after Gaussian blurring? What does it do in the presence of noise, given the curse of dimensionality? OpenCog integrates PLN and MOSES (~2005). "Interpretable Model-Based Hierarchical RL Using Inductive Logic Programming" (2021) https://news.ycombinator.com/item?id=37463686 https://news.ycombinator.com/item?id=37463686 : > https://en.wikipedia.org/wiki/Probabilistic_logic_network https://en.wikipedia.org/wiki/Probabilistic_logic_network : >> The basic goal of PLN is to provide reasonably accurate probabilistic inference in a way that is compatible with both term logic and predicate logic, and scales up to operate in real time on large dynamic knowledge bases Asmoses updates an in-RAM (*) online hypergraph with the graph relations it learns. CuPy wraps CuDNN. Re: quantum logic and quantum causal inference: https://news.ycombinator.com/item?id=38721246 https://news.ycombinator.com/item?id=38721246 From https://news.ycombinator.com/item?id=39255303 https://news.ycombinator.com/item?id=39255303 : > Is Quantum Logic the correct propositional logic? Is Quantum Logic a sufficient logic for all things? A quantum ML task: Find all local and nonlocal state linkages within the presented observations And then also do universal function approximation