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Satisfaction equilibrium

From Wikipedia, the free encyclopedia

Satisfaction Equilibrium
A solution concept in game theory
Relationship
Subset ofsolution concept
Superset ofNon-cooperative game theory
Significance
Used forAll non-cooperative games

In game theory, a satisfaction equilibrium is a solution concept for a class of non-cooperative games, namely games in satisfaction form. Games in satisfaction form model situations in which players aim at satisfying a given individual constraint, e.g., a performance metric must be smaller or bigger than a given threshold. When a player satisfies its own constraint, the player is said to be satisfied. A satisfaction equilibrium, if it exists, arises when all players in the game are satisfied.

History

The term Satisfaction equilibrium (SE) was first used to refer to the stable point of a dynamic interaction between players that are learning an equilibrium by taking actions and observing their own payoffs. The equilibrium lies on the satisfaction principle, which stipulates that an agent that is satisfied with its current payoff does not change its current action. [1]

Later, the notion of satisfaction equilibrium was introduced as a solution concept for Games in satisfaction form.[2] Such solution concept was introduced in the realm of electrical engineering for the analysis of quality of service (QoS) in Wireless ad hoc networks. In this context, radio devices (network components) are modelled as players that decide upon their own operating configurations in order to satisfy some targeted QoS.

Games in satisfaction form and the notion of satisfaction equilibrium have been used in the context of the fifth generation of cellular communications (5G) for tackling the problem of energy efficiency, [3] spectrum sharing [4] and transmit power control. [5] [6] In the smart grid, games in satisfaction form have been used for modelling the problem of data injection attacks. [7]

Games in Satisfaction Form

In static games of complete, perfect information, a satisfaction-form representation of a game is a specification of the set of players, the players' action sets and their preferences. The preferences for a given player are determined by a mapping, often referred to as the preference mapping, from the Cartesian product of all the other players' action sets to the given player's power set of actions. That is, given the actions adopted by all the other players, the preference mapping determines the subset of actions with which the player is satisfied.


Definition [Games in Satisfaction Form[2]]
A game in satisfaction form is described by a tuple

where, the set , with , represents the set of players; the set , with and , represents the set of actions that player can play. The preference mapping

determines the set of actions with which player is satisfied given the actions played by all the other players. The set is the power set of .


In contrast to other existing game formulations, e.g., normal form and normal form with constrained action sets,[8] the notion of performance optimization, i.e., utility maximization or cost minimization, is not present. Games in satisfaction-form model the case in which players adopt their actions aiming to satisfy a specific individual constraint given the actions adopted by all the other players. An important remark is that, players are assumed to be careless of whether other players can satisfy or not their individual constraints.

Satisfaction Equilibrium

An action profile is a tuple . The action profile in which all players are satisfied is an equilibrium of the corresponding game in satisfaction form. At a satisfaction equilibrium, players do not exhibit a particular interest in changing its current action.


Definition [Satisfaction Equilibrium in Pure Strategies[2]]
The action profile is a satisfaction equilibrium in pure strategies for the game if for all ,

.

Satisfaction Equilibrium in Mixed Strategies

For all , denote the set of all possible probability distributions over the set by , with . Denote by the probability distribution (mixed strategy) adopted by player to choose its actions. For all , represents the probability with which player chooses action . The notation represents the mixed strategies of all players except that of player .


Definition [Extension to Mixed Strategies of the Satisfaction Form [2]] The extension in mixed strategies of the game is described by the tuple , where the correspondence

determines the set of all possible probability distributions that allow player to choose an action that satisfies its individual conditions with probability one, that is,



A satisfaction equilibrium in mixed strategies is defined as follows.


Definition [Satisfaction Equilibrium in Mixed Strategies[2]]
The mixed strategy profile is an SE in mixed strategies if for all ,

.

Let the -th action of player , i.e., , be associated with the unitary vector , where, all the components are zero except its -th component, which is equal to one. The vector represents a degenerated probability distribution, where the action is deterministically chosen. Using this argument, it becomes clear that every satisfaction equilibrium in pure strategies of the game is also a satisfaction equilibrium in mixed strategies of the game .

At an SE of the game , players choose their actions following a probability distribution such that only action profiles that allow all players to simultaneously satisfy their individual conditions with probability one are played with positive probability. Hence, in the case in which one SE in pure strategies does not exist, then, it does not exist a SE in mixed strategies in the game .

ε-Satisfaction Equilibrium

Under certain conditions, it is always possible to build mixed strategies that allow players to be satisfied with probability , for some . This observation leads to the definition of a solution concept known as -satisfaction equilibrium (-SE).


Definition: [ε-Satisfaction Equilibrium[2]]
Let satisfy . The mixed strategy profile is an epsilon-satisfaction equilibrium (-SE) of the game , if for all , it follows that

,

where



From the definition above, it can be implied that if the mixed strategy profile is an -SE, it holds that,

That is, players are unsatisfied with probability . The relevance of the -SE is that it models the fact that players can be tolerant a certain unsatisfaction level. At a given -SE, none of the players is interested in changing its mixed strategy profile as long as it is satisfied with a probability higher than or equal to , for some .

In contrast to the conditions for the existence of a SE in either pure or mixed strategies, the conditions for the existence of an -SE are mild.


Proposition [Existence of an -SE[2]]
Let , be a finite game in satisfaction form. Then, if for all , there always exists an action profile such that

,

then there always exists a strategy profile and a real , with , such that, is an -SE.


Equilibrium Selection

Games in satisfaction form might exhibit several satisfaction equilibria. In such a case, players might associate to each of their own actions a value representing the effort or cost to play such action. From this perspective, if several SEs exist, players might prefer the one that requires the lowest (global or individual) effort or cost. To model this preference, games in satisfaction form might be equipped with cost functions for each of the players.

For all , let the function determine the effort or cost paid by player for using each of its actions. More specifically, given a pair of actions , the action is preferred against by player if

Note that this preference for player is independent of the actions adopted by all the other players.


Definition: [Efficient Satisfaction Equilibrium (ESE)]
Let be the set of satisfaction equilibria in pure strategies of the game in satisfaction form . The strategy profile is an efficient satisfaction equilibrium if for all , it follows that

.

In the trivial case in which for all the function is a constant function, the set of ESE and the set of SE are identical. This highlights the relevance of the ability of players to differentiate the effort of playing one action or another in order to select one (satisfaction) equilibrium among all the existing equilibria.

In games in satisfaction form with nonempty sets of satisfaction equilibria, when all players assign different costs to its actions, i.e., for all and for all , it holds that , there always exists an ESE. Nonetheless, it is not necessarily unique, which implies that there still exists room for other equilibrium refinements beyond the notion of individual cost functions. [5] [6]

Generalizations

Games in satisfaction form for which it does not exists an action profile in which all players are satisfied are said not to possess a satisfaction equilibrium. In this case, an action profile induces a partition of the set formed by the sets and . On one hand, the players in are satisfied. On the other hand, players in are unsatisfied. If players in the set cannot be satisfied by any of its actions given the actions of all the other players, these players are not interested in changing its current action. This implies that action profiles that satisfy this condition are also equilibria. This is because none of the players is particularly interested in changing their current actions, even those that are unsatisfied. This reasoning led to another solution concept known as generalized satisfaction equilibrium (GSE). This generalization is proposed in the context of a novel game formulation, namely the generalized satisfaction form. [9]


Definition: [Generalized Satisfaction Form]
A game in generalized satisfaction form is described by a tuple , where, the set , with , represents the set of players; the set , with and , represents the set of actions that player can play; and the preference mapping

,

determines the set of probability mass functions (mixed strategies) with support that satisfy player given the mixed strategies adopted by all the other players.


The generalized satisfaction equilibrium is defined as follows.


Definition: [Generalized Satisfaction Equilibrium (GSE)[9]]
The mixed strategy profile is a generalized satisfaction equilibrium of the game in generalized satisfaction form if there exists a partition of the set formed by the sets and and the following holds:
(i) For all , ; and
(ii)For all ,


Note that the GSE boils down to the notion of -SE of the game in satisfaction form when, and for all , the correspondence is chosen to be

with . Similarly, the GSE boils down to the notion of SE in mixed strategies when and . Finally, note that any SE is a GSE, but the converse is not true.

References

  1. ^ Ross, S.; Chaib-draa, B. (May 2006). "Satisfaction Equilibrium: Achieving Cooperation in Incomplete Information Games". Proceedings of the Canadian Conference on Artificial Intelligence. Ottawa, ON, Canada. doi:10.1007/11766247_6.
  2. ^ a b c d e f g Perlaza, S.; Tembine, H.; Lasaulce, S.; Debbah, M. (April 2012). "Quality-Of-Service Provisioning in Decentralized Networks: A Satisfaction Equilibrium Approach". IEEE Journal of Selected Topics in Signal Processing. 6 (2): 104–116. arXiv:1112.1730. doi:10.1109/JSTSP.2011.2180507. S2CID 9567688.
  3. ^ Elhammouti, H.; Sabir, E.; Benjillali, M.; Echabbi, L.; Tembine, H. (September 2017). "Self-Organized Connected Objects: Rethinking QoS Provisioning for IoT Services". IEEE Communications Magazine. 55 (9): 41–47. doi:10.1109/MCOM.2017.1600614. S2CID 27329276.
  4. ^ Southwell, R.; Chen, X.; Huang, J. (March 2014). "Quality of Service Games for Spectrum Sharing". IEEE Journal on Selected Areas in Communications. 32 (3): 589–600. arXiv:1310.2354. doi:10.1109/JSAC.2014.1403008. S2CID 9227076.
  5. ^ a b Promponas, P.; Tsiropoulou, E-E.; Papavassiliou, S. (May 2021). "Rethinking Power Control in Wireless Networks: The Perspective of Satisfaction Equilibrium". IEEE Transactions on Control of Network Systems. 8 (4): 1680–1691. doi:10.1109/TCNS.2021.3078123. S2CID 236728675.
  6. ^ a b Promponas, P.; Pelekis, C.; Tsiropoulou, E-E.; Papavassiliou, S. (July 2021). "Games in Normal and Satisfaction Form for Efficient Transmission Power Allocation Under Dual 5G Wireless Multiple Access Paradigm". IEEE/ACM Transactions on Networking. 29 (6): 2574–2587. doi:10.1109/TNET.2021.3095351. S2CID 237965568.
  7. ^ Sanjab, A.; Saad, W. (July 2016). "Data Injection Attacks on Smart Grids With Multiple Adversaries: A Game-Theoretic Perspective". IEEE Transactions on Smart Grid. 7 (4): 2038–2049. arXiv:1604.00118. doi:10.1109/TSG.2016.2550218. S2CID 14309194.
  8. ^ Debreu, G. (October 1952). "A Social Equilibrium Existence Theorem" (PDF). Proceedings of the National Academy of Sciences of the United States of America. 38 (10): 886–893. doi:10.1073/pnas.38.10.886. PMC 1063675. PMID 16589195.
  9. ^ a b Goonewardena, M.; Perlaza, S.; Yadav, A.; Ajib, W. (June 2017). "Generalized Satisfaction Equilibrium for Service-Level Provisioning in Wireless Networks". IEEE Transactions on Communications. 65 (6): 2427–2437. doi:10.1109/TCOMM.2017.2662701. S2CID 25391577.
This page was last edited on 13 July 2022, at 18:50
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