## 3 Applications of Game Theory in WSN
### Other Uses of Game Theory in WSN  
#### 3.5.1 Evolutionary and Soft Computing  
Researchers also attempted to use GA for WSN in other aspects. For instance, [PERSON] _et al_. [192] proposed Game Optimization CSMA (GO/CSMA) to optimize CSMA mechanism. [PERSON] and [PERSON] [74] used GT model to realize NE and node set's rational division. [PERSON] _et al_. [193] first proposed an autonomic management framework (ASGrid) to smooth the integration of WSN and grid systems. [PERSON] _et al_. [194] developed an agent-based negotiable game theoretic sensor management (ANGSm) approach incorporating sub-game NE into negotiation. Holes, hindering the information flow in WSN, happen when one or more sensors are not functioning or few sensors are missing during deployment in any designated area. [PERSON] [195] presented the potential game model for detecting holes in WSN. A coverage optimization problem for mobile visual sensor networks as a repeated multi-player game was formulated. A synchronous distributed learning algorithm where each sensor only remembers its own utility values and actions played during the last two time steps was presented in literatures [196, 197]. [PERSON] _et al_. [198] proposed a technique to implement self-organization strategies for WSN. The process of iterating the computation of the Voronoi diagram generated by the sensors has a maximum fixed point which corresponds to the NE of a strategic game where sensor nodes move iteratively to the centers of the Voronoi cells. This fixed-point represents the best deployment that can be achieved from the coverage point of view. [PERSON] _et al_. [199] applied evolutionary games to non-cooperative networks containing a large number of individual non-cooperative terminals or sensors and proposed some guidelines for designing a framework that supports evolution of protocols. A pricing and payment technique was presented in [200] to obtain an optimal path in a WSN by considering reliability, energy and traffic load. The proposed algorithm is able to find a path which improves network lifetime, load distribution and path reliability. A robust design using fuzzy interpolation in the viewpoint of GT was given in [201]. The fuzzy approximation error for the nonlinear dynamics of multiple sources is incorporated into the design. [PERSON] _et al_. [202] proposed a distributed algorithm which is based on the non-cooperative game principle. [PERSON] and [PERSON] [22] introduced the concept of multi-class wireless sensor networks where each class is governed by a different authority to study the evolution of cooperation in static and mobile multi-class WSN using evolutionary game theory. The proposed algorithm, called Patient Grim Strategy, provides an NE solution to the game theoretic problem of cooperation in multi-class static wireless sensor networks. [PERSON] _et al_. [203] introduced a novel game theoretical approach to the sensor management problem considering each node as an intelligent agent and using the concepts of the theory of auctions. [PERSON] _et al_. [204] proposed a Distributed Source-Relay Assignment (DSRA) algorithm for competitive price adjustment. A two-side market game approach is employed to jointly consider the benefits of all sources and relays. The equilibrium concept in such games is called the core. The outcomes in the core of the game cannot be improved upon by any subset of players. These outcomes correspond exactly to the price-lists that competitively balance the benefits of all sources and relays. The core of the game is defined as discrete core when the price assumes only discrete values. A patient is equipped with health parameter transducers which are connected to a WSN. Moreover, the WSN will perform somecomputations and will raise an alarm when some diseases are suspected [205]. A distributed algorithm, _i.e._, the decision may be done by any more dealing with the disease detection, is proposed to solve the problem. [PERSON] and [PERSON] [206] presented a signaling game-theoretic model to analyze intrusion detection in WSN.