In[]:=
mwtmrule[rules_]:=<|"StateEvolutionFunction"((Function[ru,TuringMachine[ru][#]]/@rules)&),"StateEquivalenceFunction"SameQ,"StateEventFunction"Identity,"EventDecompositionFunction"Identity,"EventApplicationFunction"Identity,"SystemType""TuringMachine","EventSelectionFunction"Identity|>
In[]:=
ResourceFunction["MultiwaySystem"][mwtmrule[Range[5]],{{{1,1,0},{0,0,0,0}}},6,"StatesGraphStructure"]
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In[]:=
ResourceFunction["MultiwaySystem"][mwtmrule[Range[0,20]],{{{1,1,0},{0,0,0,0}}},6,"StatesGraphStructure"]
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In[]:=
ResourceFunction["MultiwaySystem"][mwtmrule[Range[0,30]],{{{1,1,0},{0,0,0,0}}},6,"StatesGraphStructure"]
Out[]=
In[]:=
ResourceFunction["MultiwaySystem"][mwtmrule[Range[2000,2010]],{{{1,1,0},{0,0,0,0}}},6,"StatesGraphStructure"]
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In[]:=
ResourceFunction["MultiwaySystem"][mwtmrule[Range[0,4095]],{{{1,1,0},{0,0,0,0}}},2,"StatesGraphStructure"]
Out[]=
In[]:=
LayeredGraphPlot[%108,AspectRatio1/3]
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In[]:=
ResourceFunction["MultiwaySystem"][mwtmrule[Range[0,4095]],{{{1,1,0},{0,0,0,0}}},2,"CausalInvariantQ"]
Out[]=
True
In[]:=
ResourceFunction["MultiwaySystem"][mwtmrule[Range[0,4095]],{{{1,1,0},{0,0,0,0}}},2,"StatesGraph","StateRenderingFunction"Inherited]
Out[]=
In[]:=
ResourceFunction["MultiwaySystem"][mwtmrule[Range[0,4095]],{{{1,1,0},{0,0,0,0}}},2,"StatesGraphStructure","IncludeEventInstances"True]
Out[]=
In[]:=
ResourceFunction["MultiwaySystem"][mwtmrule[Range[0,4095]],{{{1,1,0},{0,0,0,0}}},2,"StatesGraphStructure","IncludeStatePathWeights"True]
Out[]=
$Aborted
In[]:=
ResourceFunction["MultiwaySystem"][mwtmrule[Range[0,4095]],{{{1,1,0},{0,0,0,0}}},2,"StatesGraphStructure"]
Out[]=
These are the nearby states in rulial space.... I.e. small change in “algorithm” takes one to each different state
[[[ What is multiway causal graph like? ]]]

? Also consider all possible initial conditions

The Structure of Maximally Non-Deterministic Turing Machine Space AKA Turing Machine Rulial Space

? Consider subsets of TMs: e.g. symmetric rules