In mathematics, Blackwell's contraction mapping theorem provides a set of sufficient conditions for an operator to be a contraction mapping. It is widely used in areas that rely on dynamic programming as it facilitates the proof of existence of fixed points. The result is due to David Blackwell who published it [1] in 1965 in the Annals of Mathematical Statistics.
Let
T
X
T:X → X
\beta
(monotonicity) u\leqv\impliesTu\leqTv
(discounting) T(u+c)\leqTu+\betac.
For all
u
v\inX
u\leqv+||v-u||
T(u)\leqT(v+||v-u||)\leqT(v)+\beta||v-u||
T(u)-T(v)\leq\beta||v-u||
T
An agent has access to only one cake for its entire, infinite, life. It has to decide the optimal way to consume it. It evaluates a consumption plan,
ct
infty | |
\sum | |
t=0 |
\betat
| |||||||
1-\sigma |
\beta\in(0,1)
max | |
ct |
infty | |
\sum | |
t=0 |
\betat
| |||||||
1-\sigma |
subjecttoxt=xt-1-ct,x-1=0,ct\geq0andxt\geq0\forallt\inZ+
Applying Bellman's principle of optimality we find 's corresponding Bellman equation
V(c)=maxc'
c1-\sigma | |
1-\sigma |
+\betaV(c')
It can be proven that the solution to this functional equation, if it exists, is equivalent to the solution of .[2] To prove its existence we can resort to Blackwell's sufficient conditions.
Define the operator
T(V(c))=maxc'
c1-\sigma | |
1-\sigma |
+\betaV(c')
First note that
T
infty | |
\sum | |
t=0 |
\betat
| |||||||
1-\sigma |
\leq
infty | |
\sum | |
t=0 |
\betat
11-\sigma | |
1-\sigma |
=
1 | |
(1-\beta)(1-\sigma) |
<infty
ifV(c)\geqU(c)\forallc\in[0,1]
T(V(c))=maxc'
c1-\sigma | |
1-\sigma |
+\betaV(c')\geqmaxc'
c1-\sigma | |
1-\sigma |
+\betaU(c')=T(U(c))
T(V(c)+a)=maxc'
c1-\sigma | |
1-\sigma |
+\beta(V(c')+a)\leqmaxc'
c1-\sigma | |
1-\sigma |
+\betaV(c')+\betaa=T(V(c))+\betaa
a