LeanMachineLearning exposition

Learning.sumRewards_zero๐Ÿ”—

This page has the declaration's own card below, then its dependency graph, then a card for each dependency (type dependencies first, then the rest of the transitive closure). For a theorem, the graph and the dependency cards only follow its statement's dependencies (its proof is replaced by sorry, so what it proves doesn't depend on how); for everything else, both the type and the body/value are followed, since their content is part of what later declarations build on.

Minimal Lean file

sumRewards_zero๐Ÿ”—

LemmaLearning.sumRewards_zero

No docstring.

๐Ÿ”—theorem
Learning.sumRewards_zero.{u_1, u_3} {๐“ : Type u_1} {ฮฉ : Type u_3} [DecidableEq ๐“] {A : โ„• โ†’ ฮฉ โ†’ ๐“} {a : ๐“} {R' : โ„• โ†’ ฮฉ โ†’ โ„} : sumRewards A R' a 0 = 0
Learning.sumRewards_zero.{u_1, u_3} {๐“ : Type u_1} {ฮฉ : Type u_3} [DecidableEq ๐“] {A : โ„• โ†’ ฮฉ โ†’ ๐“} {a : ๐“} {R' : โ„• โ†’ ฮฉ โ†’ โ„} : sumRewards A R' a 0 = 0

Code

lemma sumRewards_zero {R' : โ„• โ†’ ฮฉ โ†’ โ„} : sumRewards A R' a 0 = 0
Type uses (1)
Used by (3)

Actions: Source ยท Open Issue

Proof
by ext; simp [sumRewards]

Dependency graph

Type dependencies (1)

sumRewards๐Ÿ”—

DefinitionLearning.sumRewards

Sum of rewards obtained when pulling action a up to time t (exclusive).

๐Ÿ”—def
Learning.sumRewards.{u_1, u_3} {๐“ : Type u_1} {ฮฉ : Type u_3} [DecidableEq ๐“] (A : โ„• โ†’ ฮฉ โ†’ ๐“) (R' : โ„• โ†’ ฮฉ โ†’ โ„) (a : ๐“) (t : โ„•) (ฯ‰ : ฮฉ) : โ„
Learning.sumRewards.{u_1, u_3} {๐“ : Type u_1} {ฮฉ : Type u_3} [DecidableEq ๐“] (A : โ„• โ†’ ฮฉ โ†’ ๐“) (R' : โ„• โ†’ ฮฉ โ†’ โ„) (a : ๐“) (t : โ„•) (ฯ‰ : ฮฉ) : โ„

Code

def sumRewards (A : โ„• โ†’ ฮฉ โ†’ ๐“) (R' : โ„• โ†’ ฮฉ โ†’ โ„) (a : ๐“) (t : โ„•) (ฯ‰ : ฮฉ) : โ„ :=
  โˆ‘ s โˆˆ range t, if A s ฯ‰ = a then R' s ฯ‰ else 0
Used by (44)

Actions: Source ยท Open Issue