In this paper, we study a variant of hedonic games, called . The model is defined by a bijection from agents with preferences for each other to vertices in a graph . The utility of an agent depends on the neighbors assigned in the graph. More precisely, it is the sum over all neighbors of the preferences that the agent has towards the agent assigned to the neighbor. We first consider the price of stability and fairness for different classes of preferences. In particular, we show that there is an instance such that the price of fairness ({\sf PoF}) is unbounded in general. Moreover, we show an upper bound and an almost tight lower bound of {\sf PoF}, where is the average degree of an input graph. Then we investigate the computational complexity of problems to find certain ``good’’ seat arrangements, say , , , and . We give dichotomies of computational complexity of four problems from the perspective of the maximum order of connected components in an input graph. For the parameterized complexity, can be solved in time , while it cannot be solved in time under ETH, where is the number of agents and is the vertex cover number of an input graph. Moreover, we show that and are weakly NP-hard even on graphs of bounded vertex cover number. Finally, we prove that determining whether a stable arrangement can be obtained from a given arrangement by swaps is W[1]-hard when parameterized by , whereas it can be solved in time .

生成讲解博客的中文版本

生成AI智能校验的中文版本