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Cslib/Computability/Machines/ComputationModel/Basic.lean
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| /- | ||
| Copyright (c) 2026 Maximilian Keßler. All rights reserved. | ||
| Released under Apache 2.0 license as described in the file LICENSE. | ||
| Authors: Maximilian Keßler | ||
| -/ | ||
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| module | ||
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| public import Mathlib.Algebra.Polynomial.Eval.Defs | ||
| public import Mathlib.Data.ENat.Lattice | ||
| public import Mathlib.Logic.Function.Iterate | ||
| public import Cslib.Foundations.Data.RelatesInSteps | ||
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| /-! # Transition Based Computation Models | ||
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| Defines typeclasses and definitions for computation systems based on a transition function | ||
| `step : cfg → Option cfg`, where `cfg` is the type of configurations of such a system. | ||
| Additionally, we bundle this with input/output functions from/to words over an alphabet | ||
| to obtain a model of computation between lists of symbols that has a notion of execution time | ||
| (given by the needed number of applications of the `step` function). | ||
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| The main example of such a transition machine are turing machines: | ||
| Typical turing models work by inputting a word (over a fixed alphabet) | ||
| on a specific tape, then iterating a step function until an accepting state is reached, | ||
| and the output is defined as a word (potentially over a different alphabet than the input), | ||
| typically read from a specific tape. | ||
| For all such turing machines (independent of the exact design choices), we can define instances | ||
| to `TransitionMachine` and thereby use the same definitions of computation and time for all | ||
| models, and in particular state equivalences of such computation models. | ||
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| ## Design | ||
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| - Termination of such a machine is modeled by the step function yielding `none` | ||
| - We expose the alphabet types in the definition of `TransitionMachine`. | ||
| - The output function is *partial* in the sense that it can return `none`. In this case, | ||
| there is no output of a computation (this can occur even if the computation terminates). | ||
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| ## Important declarations | ||
| - `TransitionSystem τ`: Terms `(t : τ)` have an associated *configuration type* `cfg t` | ||
| - `TransitionMachine τ Γᵢ Γₒ`: In addition to this being a `TransitionSystem τ`, there is | ||
| - an input function `init : List Γᵢ → cfg t` | ||
| - an output function `output : cfg t → Option (List Γₒ)` | ||
| - `OutputsInTime t n l l'`: States that `t` outputs `l'` from `l` in at most `n` steps. | ||
| - `ComputesInPolyTime t f`: The machine `t` computes the function `f : List Γᵢ → List Γₒ` in | ||
| polynomial time. | ||
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| ## TODO: | ||
| It might be useful to work with `ℕ∞` instead of `ℕ` for predicates such as `EvalsToInTime`. | ||
| This would allow us to recover the regular notion of `EvalsTo` (without time constraints) | ||
| as the special case of the time bound `ω`. | ||
| We could then introduce abbreviations for `EvalsTo` or `Outputs` that insert `ω`. | ||
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| -/ | ||
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| @[expose] public section | ||
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| namespace Computation | ||
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| /-- | ||
| For each element `(t : τ)`, there is a bundle of a type `cfg t` with a step / transition function | ||
| `cfg t → Option (cfg t)`. | ||
| -/ | ||
| class TransitionSystem (τ : Type u) where | ||
| cfg (t : τ) : Type* | ||
| step {t : τ} : cfg t → Option (cfg t) | ||
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| /-- | ||
| Bundles a `TransitionSystem` with input and output functions from/to words over an alphabet. | ||
| This way, we can think of elements of `τ` as allowing computations `List Γᵢ → List Γₒ` | ||
| by lifting inputs into the computation context, iterating the `step` function, | ||
| and taking output from this computation context. | ||
| -/ | ||
| class TransitionMachine (τ : Type u) (Γᵢ Γₒ : outParam (Type v)) extends TransitionSystem τ where | ||
| init {t : τ} : List Γᵢ → cfg t | ||
| output {t : τ} : cfg t → Option (List Γₒ) | ||
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| namespace TransitionSystem | ||
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| variable {τ : Type u} [TransitionSystem τ] | ||
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| def stepRelation (t : τ) : (Option (cfg t)) → (Option (cfg t)) → Prop | ||
| | a, b => a.bind step = b | ||
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| /-- | ||
| A "proof" of the fact that `t` eventually reaches `b` when repeatedly evaluated on `a`, | ||
| remembering the number of steps it takes. | ||
| -/ | ||
| structure EvalsTo (t : τ) (a b : Option (cfg t)) where | ||
| steps : ℕ | ||
| evals : (flip bind step)^[steps] a = b | ||
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| /-- | ||
| A "proof" that `t` reaches `b` from `a` in at most `n` steps, remembering the specific number | ||
| of steps. | ||
| -/ | ||
| structure EvalsToInTime (t : τ) (a b : Option (cfg t)) (n : ℕ) extends EvalsTo t a b where | ||
| steps_le : steps ≤ n | ||
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| variable {t : τ} {a b c : Option (cfg t)} {n n₁ n₂ : ℕ} | ||
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| def EvalsTo.refl : EvalsTo t a a where | ||
| steps := 0 | ||
| evals := rfl | ||
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| def EvalsTo.trans (h₁ : EvalsTo t a b) (h₂ : EvalsTo t b c) : EvalsTo t a c where | ||
| steps := h₂.steps + h₁.steps | ||
| evals := by rw [Function.iterate_add_apply, h₁.evals, h₂.evals] | ||
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| def EvalsToInTime.refl : EvalsToInTime t a a 0 where | ||
| toEvalsTo := EvalsTo.refl | ||
| steps_le := by rfl | ||
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| def EvalsToInTime.trans (h₁ : EvalsToInTime t a b n₁) (h₂ : EvalsToInTime t b c n₂) : | ||
| EvalsToInTime t a c (n₂ + n₁) where | ||
| toEvalsTo := EvalsTo.trans h₁.toEvalsTo h₂.toEvalsTo | ||
| steps_le := add_le_add h₂.steps_le h₁.steps_le | ||
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| def EvalsToInTime.of_le (h : EvalsToInTime t a b n₁) (hn : n₁ ≤ n₂) : | ||
| EvalsToInTime t a b n₂ where | ||
| toEvalsTo := h.toEvalsTo | ||
| steps_le := le_trans h.steps_le hn | ||
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| end TransitionSystem | ||
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| namespace TransitionMachine | ||
| open TransitionSystem | ||
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| variable {τ : Type*} {Γᵢ Γₒ : Type} [TransitionMachine τ Γᵢ Γₒ] | ||
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| /-- | ||
| The transition machine `t` outputs `l'` on input `l`. | ||
| -/ | ||
| structure Outputs (t : τ) (l : List Γᵢ) (l' : List Γₒ) where | ||
| haltState : (cfg t) | ||
| haltState_halts : TransitionSystem.step haltState = none | ||
| evalsTo : TransitionSystem.EvalsTo t (some (init l)) (some haltState) | ||
| output_eq : output haltState = some l' | ||
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| /-- | ||
| The transition machine `t` outputs `l'` on input `l` in at most `n` steps. | ||
| -/ | ||
| structure OutputsInTime (t : τ) (n : ℕ) (l : List Γᵢ) (l' : List Γₒ) where | ||
| haltState : (cfg t) | ||
| haltState_halts : TransitionSystem.step haltState = none | ||
| evals_to : TransitionSystem.EvalsToInTime t (some (init l)) (some haltState) n | ||
| output_eq : output haltState = some l' | ||
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| /-- | ||
| Time bounds of `OutputsInTime` can be increased. | ||
| -/ | ||
| def OutputsInTime.of_le {t : τ} {n m : ℕ} {l : List Γᵢ} {l' : List Γₒ} (hnm : n ≤ m) | ||
| (hv : OutputsInTime t n l l') : OutputsInTime t m l l' where | ||
| haltState := hv.haltState | ||
| haltState_halts := hv.haltState_halts | ||
| evals_to := TransitionSystem.EvalsToInTime.of_le hv.evals_to hnm | ||
| output_eq := hv.output_eq | ||
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| /-- | ||
| The output of any computation of transition machines is unique. | ||
| -/ | ||
| lemma OutputsInTime.output_unique {t : τ} {n₁ n₂ : ℕ} {l : List Γᵢ} {l'₁ l'₂ : List Γₒ} | ||
| (ho₁ : OutputsInTime t n₁ l l'₁) (ho₂ : OutputsInTime t n₂ l l'₂) : | ||
| l'₁ = l'₂ := by | ||
| wlog hle : ho₁.evals_to.steps ≤ ho₂.evals_to.steps | ||
| · symm | ||
| exact this ho₂ ho₁ (Nat.le_of_not_le hle) | ||
| · have : ho₁.evals_to.steps = ho₂.evals_to.steps := by | ||
| obtain ⟨d, hd⟩ := Nat.exists_eq_add_of_le' hle | ||
| cases d with | ||
| | zero => symm; simpa using hd | ||
| | succ d' => | ||
| have := ho₂.evals_to.evals | ||
| rw [hd, Function.iterate_add_apply, ho₁.evals_to.evals, | ||
| Function.iterate_succ_apply, Option.bind_eq_bind, flip, Option.bind_some, | ||
| ho₁.haltState_halts, Function.iterate_fixed rfl] at this | ||
| contradiction | ||
| have : ho₁.haltState = ho₂.haltState := by | ||
| apply Option.some.inj | ||
| rw [← ho₁.evals_to.evals, ← ho₂.evals_to.evals, this] | ||
| rw [← Option.some_inj, ← ho₁.output_eq, ← ho₂.output_eq, this] | ||
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| /-- | ||
| "Proof" that the transition system `t` computes the function `f` in polynomial time. | ||
| The witness polynomial is bundled as part of this structure. | ||
| -/ | ||
| structure ComputesInPolyTime (t : τ) (f : List Γᵢ → List Γₒ) where | ||
| time : Polynomial ℕ | ||
| outputsFun : ∀ w, OutputsInTime t (time.eval w.length) w (f w) | ||
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| end TransitionMachine | ||
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| end Computation | ||
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First, I don't understand why you need the
cfgfield. What's wrong with droppingcfgand replacing everycfg tbyτ? In general, it's more hassle dealing with a family of types than just a single type.Second, there is already a theory of partial function is mathlib:
https://leanprover-community.github.io/mathlib4_docs/Mathlib/Data/PFun.html
Any reason you want to develop your own theory of partial functions?