# Fixed Point Theorems for Random Lowersemi-continuous Mappings

- Raúl Fierro
^{1, 2}, - Carlos Martínez
^{1}and - Claudio H. Morales
^{3}Email author

**2009**:584178

**DOI: **10.1155/2009/584178

© Raúl Fierro et al. 2009

**Received: **31 January 2009

**Accepted: **1 July 2009

**Published: **3 August 2009

## Abstract

We prove a general principle in Random Fixed Point Theory by introducing a condition named ( ) which was inspired by some of Petryshyn's work, and then we apply our result to prove some random fixed points theorems, including generalizations of some Bharucha-Reid theorems.

## 1. Introduction

Let be a metric space and a closed and nonempty subset of . Denote by (resp., ) the family of all nonempty (resp., nonempty and closed) subsets of . A mapping is said to satisfy if, for every closed ball of with radius and any sequence in for which and as , there exists such that where . If is any nonempty set, we say that the operator satisfies if for each , the mapping satisfies . We should observe that this latter condition is related to a condition that was originally introduced by Petryshyn [1] for single-valued operators, in order to prove existence of fixed points. However, in our case, the condition is used to prove the measurability of a certain operator. On the other hand, in the year 2001, Shahzad (cf. [2]) using an idea of Itoh (cf. [3]), see also ([4]), proved that under a somewhat more restrictive condition, named condition (A), the following result.

Theorem 1 S.

Let be a nonempty separable complete subset of a metric space and a continuous random operator satisfying condition (A). Then has a deterministic fixed point if and only if has a random fixed point.

We shall show that the above result is still valid if the operator is only lower semi-continuous. In addition, the assumption that each value is closed has been relaxed without an extra assumption. Furthermore we state a new condition which generalizes condition (A) and allow us to generalize several known results, such as, Bharucha-Reid [5, Theorem 7], Domínguez Benavides et al. [6, Theorem 3.1] and Shahzad [2, Theorem 2.1].

## 2. Preliminaries

Let be a measurable space and let be a metric space. A mapping , is said to be measurable if is measurable for each open subset of . This type of measurability is usually called weakly (cf. [7]), but since this is the only type of measurability we use in this paper, we omit the term "weakly". Notice that if is separable and if, for each closed subset of , the set is measurable, then is measurable.

Let be a nonempty subset of and , then we say that is lower (upper) semi-continuous if is open (closed) for all open (closed) subsets of . We say that is continuous if is lower and upper semi-continuous.

A mapping is called a random operator if, for each , the mapping is measurable. Similarly a multivalued mapping is also called a random operator if, for each , is measurable. A measurable mapping is called a measurable selection of the operator if for each . A measurable mapping is called a random fixed point of the random operator (or ) if for every (or ). For the sake of clarity, we mention that

Let
be a closed subset of the Banach space
, and suppose that
is a mapping from
into the topological vector space
. We say the
is *demiclosed* at
if, for any sequences
in
and
in
with
,
converges weakly to
and
converges strongly to
, then it is the case that
and
. On the other hand, we say that
is *hemicompact* if each sequence
in
has a convergent subsequence, whenever
as
.

## 3. Main Results

Theorem 3.1.

Then has a random fixed point.

Proof.

Since , we conclude that is measurable. Additionally, we show that is closed for each . To see this, let such that . Then, let be a degenerated ball centered at and radius , and since , implies that . Hence and thus by the Kuratowski and Ryll-Nardzewski Theorem [8], has a measurable selection such that for each .

As a consequence of Theorem 3.1, we derive a new result for a lower semi-continuous random operator.

Theorem 3.2.

Then has a random fixed point.

Proof.

and consequently, . Therefore, is open, and proof is complete.

We observe that if the mapping is upper semi-continuous, then not necessarily the mapping is lower semi-continuous. Consider the following example.

Then for while , which is upper semi-continuous. On the other hand, is not lower semi-continuous.

Now, we derive several consequences of Theorem 3.2. We first obtain an extension of one of the main results of [6].

Theorem 3.3.

Then has a random fixed point.

Proof.

Hence, the demiclosedness of implies that , and thus enjoys .

Before we give an extension of the main result of [4], we observe that is basically applied to those closed balls directly used to prove the measurability of the mapping , as will be seen in the proof of the next result.

Theorem 3.4.

then has a random fixed point.

Proof.

Hence, . Since is arbitrary and is closed, we derive that , and thus satisfies .

Corollary 3.5.

Then has a random fixed point.

Proof.

Therefore, is measurable.

Next, we get a stochastic version of Schauder's Theorem, which is also an extension of a Theorem of Bharucha-Reid (see [5, Theorem 10]). We also observe that our proof is much easier and quite short.

Corollary 3.6.

Let be a compact and convex subset of a Fréchet space , and let be a continuous random operator. Then has a random fixed point.

Proof.

As we know, every Fréchet space is a complete metric space, and since is compact, itself is a complete separable metric space. In addition, for each , there exists such that . This means that the set , defined in Theorem 3.1, is nonempty. Since is compact, any sequence in contains a convergent subsequence, which means that is trivially a hemicompact operator. Consequently, by Theorem 3.4, has a random fixed point.

*random contraction*if there exists a mapping such that

Theorem 3.7.

Let be a complete separable metric space, and let be a continuous random operator such that is a contraction with constant for each . Then has a unique random fixed point.

Proof.

Then is a sequence of measurable functions. Since , the fact that is a contraction implies that . Therefore, the mapping is measurable, which completes the proof.

As a direct consequence of Theorem 3.7, we derive the extension mentioned earlier where the space is more general, and the randomness on the mapping has been removed.

Corollary 3.8.

Let be a complete separable metric space, and let be a random contraction operator with constant for each . Then has a unique random fixed point.

Next, one can derive a corollary of the proof of Theorem 3.7, which is a theorem of Hans [9].

Corollary 3.9.

Let be a complete separable metric space, and let be a continuous random operator. Suppose, for each , that there exists such that is a contraction with constant . Then has a unique random fixed point.

Proof.

As in the proof of the theorem, the mapping has a unique fixed point for each . The rest of the proof follows the proof of the theorem with the appropriate changes of the second power of by the power of .

Notice that Theorem 3.7 holds for single-valued operators. The following question is formulated for multivalued operators taking closed and bounded values in .

Open Question

Suppose that is a complete separable metric space, and let be a continuous random operator such that is a contraction with constant for each . Then does have a unique random fixed point?

## Declarations

### Acknowledgments

This work was partially supported by Dirección de Investigación e Innovación de la Pontificia Universidad Católica de Valparaíso under grant 124.719/2009. In addition, the first author was supported by Laboratory of Stochastic Analysis PBCT-ACT 13.

## Authors’ Affiliations

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