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In this paper, we study an approach to environmental topics, through multicriteria partial cooperative games. In general, not all players wish to cooperate to solve a common problem, so we consider a model where only some decision-makers cooperate. Starting from the transformation of a coalition game into a strategic one, we give a new concept of solution for partial cooperative models proving an existence theorem.

Environmental pollution and the consequent climate change have induced many game theorists to study these topics through mathematical games. When players (countries, regions, etc.) cooperate, each player pollutes less than under a non cooperative behavior and the more the cooperating countries, the greater the total benefit. An example is the pollution of shallow lakes, an interesting question studied in [

In our models, we consider n players where some work together, so we speak of partial cooperative games. These models arise from the observation of real life.

This is the ancient problem named “The tragedy of Commons” [

Is it possible for individuals to cooperate without being compelled by a law? (see [

In order to contain the emissions of pollutants, in 1997 the Kyoto Protocol to the “Framework Convention on Climate Change” limited emissions of carbon dioxide, methane, nitrous oxide, halocarbons, perfluorocarbons and sulfur hexafluoride, but the pollution problem is far from being solved satisfactorily.

Many environmental problems are studied in [

An interesting approach was made in [

Over the past few years, many game theorists were interested in the problem of coalition formation (see [

It seems to us that the mathematical game theory offers a natural medium to the study of environmental models. Our approach to such a problem is to study a cooperative situation modeled by a coalitional game

In the applications to real life, it is natural to consider multicriteria situations, because a player wishes to “optimize” multiple criteria. For example, one problem is to reduce pollution and to increase production, two objectives which are often opposed or not compatible. In the classic approach to TU-games, an allocation rule is defined to predict how rational players distribute among them the gain from cooperation. In our model, we study a game where players have multiple criteria “to optimize” and propose a new concept of solution (coalitional Pareto equilibrium), using an allocation rule to define the players’ payoff.

About multicriteria or vector games, see [

In the text, we will use equally the words “multicriteria” or “multiobjective” or “vector” games. We will use “multicriteria partial cooperative games” or “multiobjective environmental games” when only a proper subset of N is formed by cooperating players.

This paper is organized as follows: in Section 2, we set up notations and known results which will be useful for our model, in Section 3, we describe a non-cooperative model called participation game inspired by Monderer and Shapley’s model [

In this section we consider multiobjective problems that are models where the decision makers have many objectives “to optimize”.

Let

Analogously we define

Let us consider a multiobjective (or multicriteria) TU-game

In an environmental game, if all players cooperate, the grand coalition forms and obtains the best (we will specify the meaning in the next pages).

Let us write

Definition 2.1 A multicriteria game

Definition 2.2 We call i a dummy player if

Now let us define one solution for a cooperative game: the Shapley value. It was introduced by Shapley in the fifties. It is one of the most interesting solution concepts in the cooperative game theory. Intuitively it has a link with the average of the marginal contributions of each player joing (see [

Definition 2.3 The Shapley value of

where s and n denote the cardinality of the coalitions S and N respectively.

Keep in mind that an allocation rule

A “good” allocation rule verifies the following axioms:

1) Efficiency property (EFF for short):

2) Weak Monotonicity property (WMON for short): given two games

3) Dummy Out property (DUMOUT for short): for all

The Shapley value verifies the three axioms written.

To explain better the notations, let us consider the following:

Example 2.1 Let

where we mean

The first objective is the reduction of pollution percentage and the second is the increase of industrial production. If player (industry) 1 decides to act alone, its production increases by 15% but it can reduce its pollution only by 10%. If player 1 cooperates with player 2 (a second industry), their production increases by 50% and they can reduce their pollution combined by 40%... If all players cooperate, they increase their production by 80% and reduce their pollution of 90%. The Shapley value for this bi-criteria game is:

Let us consider a multicriteria non cooperative game _{i} is the payoff function of player i,

For

To define environmental games and a solution for them, we need one for cooperative games (for example the aforementioned Shapley value) as well as one for non cooperative games. To this end, we remember the definition of Pareto equilibrium (PE for short), which is the commonly used solution for (non-cooperative) multiobjective games.

Deﬁnition 2.4 Let G be a multicriteria non-cooperative game.

A strategy proﬁle

1) weak Pareto equilibrium if

2) strong Pareto equilibrium if

The set of weak and strong Pareto equilibria will be denoted by wPE and sPE respectively.

Intuitively ^{ }is a weak (strong) Pareto equilibrium for the game G if there isn’t a

Example 2.2 Let G be the bicriteria non cooperative game in the table below

Two countries (players) have two strategies: to reduce their sulphur dioxide emissions (C) or not to reduce (nC).

They have two objectives to pursue: to save the cost of the national health institute and to increase the people health.

In pure strategies the equilibria are:

In this paper we are not interested in mixed strategies.

There are no doubts that we must reduce the pollution following carbon dioxide emissions. One of the most serious problems is the contribution of each country. In this paper we suggest such models and a solution (the coalitional Pareto equilibrium) as will enable all countries to obtain the best through cooperation.

In many practical situations, the interaction among decision-makers may be a mix of cooperative and non- cooperative behavior.

Although the players in the same coalition cooperate, there are also coalitions made up of only one player. Furthermore diﬀerent coalitions do not cooperate with each other.

In such models we speak of partial cooperative games or environmental games (about partial cooperation, see [

Let us consider

By

We can define the non cooperative participation game in normal form

The utility function for player i is defined as follows:

where

Intuitively, we start with a TU-game and an allocation rule

In the following definition we generalize the concept of strong Nash equilibrium (sNE for short) to a notion of equilibrium profile for vector games. We call it coalitional Pareto equilibrium.

Deﬁnition 3.1 We say that

We note that if ^{ }is a cPE with an allocation rule, it could not be a cPE with another allocation rule. If the players have only one objective to pursue, the cPE is a sNE. (About the notion of strong Nash see [

Deﬁnition 3.2 We say that a multicriteria partial cooperative game has a partial equilibrium if there is a cPE for the corresponding participation game.

Example 3.1 Let us consider the following bicriteria game.

There are three industries (players) which work near a great shallow lake. They have pursue two objectives: the ﬁrst is the reduction of toxic substances spilt into the lake, the second is the gain of having a lake with clean water, many ﬁshes and green plants. The total cooperation give a real beneﬁt to all.

In this table we write for example:

Let the Shapley value be the allocation rule agreed upon by all players. We can use the following table to take a quick look at the coalitional Pareto equilibria (

The first two columns represent the game in example 3.1, the others represent the Shapley value relative to the game v_{S} where S is the coalition written in the ﬁrst column.

There are two cPE:

and

From Vector Optimization problems we can learn that, the m scalar games generated from breaking down the vector game, do not necessarily inherit its structure.

In fact if we break down the considered bicriteria game of the example 3.1 into two games (the ﬁrst one pertaining to the ﬁrst criterion, the second one pertaining the second criterion), we can remark that

We will now provide the following existence theorem for a coalitional Pareto equilibrium.

In the authors’ opinion this is an interesting result, because there is an incentive to cooperate: in the hypotheses of the theorem (which are often verified in the models of real life), if all players cooperate (read: if all countries cooperate), the grand coalition forms and there is an eﬃcient solution for all members.

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Theorem 3.1 Let

Proof. From deﬁnition of Shapley value and

Let us suppose, by contradiction, that

This leads us to state that there is at least a component

This is a contradiction with the properties of

Corollary 3.1 Let G be a multicriteria partial cooperative game. If

Remark 3.1 The result of theorem 3.1 is valid considering an allocation rule verifying the three axioms: EFF, WMON and DUMOUT.

Game theorists apply with success the Game Theory to environmental models and emission problems. In this paper, we consider a game where some players cooperate and others do not. We call this game “partial cooperative”. To give a new notion of solution for these games, we start trasforming the structure of a cooperative game into a strategic one. This new game is defined considering as strategies the coalitions to which player i wish to belong and the utility function assigns the Shapley value to each player who wants cooperate and

We provide a new concept of equilibrium for multiobjective environmental games, the coalitional Pareto equilibrium which generalizes the idea of strong Nash. This concept, diﬀerently from the Nash equilibrium, captures the idea of efficient equilibrium.

An existence theorem and many examples complete the paper.

As concerns possible further research, it would be interesting to study the partial cooperative problem where the allocation rule is different from the Shapley value or to consider games with utility functions in uncertainty intervals, (see [

The second author has been supported by the Gruppo Nazionale per l’Analisi Matematica, la Probabilitá e le loro Applicazioni (GNAMPA) of the Istituto Nazionale di Alta Matematica (INdAM).

GrazianoPieri,LuciaPusillo, (2015) Multicriteria Partial Cooperative Games. Applied Mathematics,06,2125-2131. doi: 10.4236/am.2015.612186