Linear-Inequality Affine Transformation Automata: Difference between revisions
(Created page with "'''Linear-Inequality Affine Transformation Automata (LIATA)''' are a model for computation based upon applying affine transformations to vectors based on cases defined by linear inequalities. They are a generalization of the rules for BMO1 and were proven to be Turing complete. == Example == An example of a LIATA are the rules for BMO1:<math display="block">f(a,b) = \begin{cases} (a-b, 4b+2) & \text{if } a > b \\ (2a+1, b-a) & \text{if } a < b \\ \end{cases}</ma...") |
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Revision as of 20:37, 30 September 2025
Linear-Inequality Affine Transformation Automata (LIATA) are a model for computation based upon applying affine transformations to vectors based on cases defined by linear inequalities. They are a generalization of the rules for BMO1 and were proven to be Turing complete.
Example
An example of a LIATA are the rules for BMO1:
This is a 2-dimension, 2-case LIATA. The 2 dimensions are the parameters a,b and the two cases are the a<b and a>b rows. For each case the parameters are transformed via an affine transformation.
Formal Definition
A n-dimension, k-case LIATA is a piecewise defined partial function :
Let a linear inequality term be any equation of the form where ~ is replaced by any (in)equality relation (=,<,≤,>,≥). Then let a linear inequality condition be any combination of linear inequality terms using logical AND, OR and NOT operations.
So, for example, the following are all linear inequality conditions:
- represented formally as
- represented formally as
- (note that we allow equalities as well)
Given a LIATA f, we say that it halts in k steps starting from configuration iff is undefined.
See Also
- @Bard's proof that 3-dim LIATA are Turing complete: Discord link
- @star's proof that 2-dim LIATA are Turing complete: Discord link