Biblio

Fractional hedonic games (FHGs) are extensively studied in game theory and explain the formation of coalitions among individuals in a group. This paper investigates the coalition generation problem, namely, finding a coalition structure whose social welfare, i.e., the sum of the players' payoffs, is maximized. We focus on agent-based methods which set the decision rules for each player in the game. Through repeated interactions the players arrive at a coalition structure. In particular, we propose CFSV, namely, coalition formation with Shapley value-based welfare distribution scheme. To evaluate CFSV, we theoretically demonstrate that this algorithm achieves optimal coalition structure over certain standard graph classes and empirically compare the algorithm against other existing benchmarks on real-world and synthetic graphs. The results show that CFSV is able to achieve superior performance.

Wireless sensor networks have achieved the substantial research interest in the present time because of their unique features such as fault tolerance, autonomous operation etc. The coverage maximization while considering the resource scarcity is a crucial problem in the wireless sensor networks. The approaches which address these problems and maximize the network lifetime are considered prominent. The node scheduling is such mechanism to address this issue. The scheduling strategy which addresses the target coverage problem based on coverage probability and trust values is proposed in Energy Efficient Coverage Protocol (EECP). In this paper the optimized decision rules is obtained by using the rough set theory to determine the number of active nodes. The results show that the proposed extension results in the lesser number of decision rules to consider in determination of node states in the network, hence it improves the network efficiency by reducing the number of packets transmitted and reducing the overhead.