Quality of Service in Network Creation Games

Network creation games model the creation and usage costs of networks formed by n selfish nodes. Each node v can buy a set of edges, each for a fixed price \alpha > 0. Its goal is to minimize its private costs, i.e., the sum (SUM-game, Fabrikant et al., PODC 2003) or maximum (MAX-game, Demaine et al., PODC 2007) of distances from $v$ to all other nodes plus the prices of the bought edges. The above papers show the existence of Nash equilibria as well as upper and lower bounds for the prices of anarchy and stability. In several subsequent papers, these bounds were improved for a wide range of prices \alpha. In this paper, we extend these models by incorporating quality-of-service aspects: Each edge cannot only be bought at a fixed quality (edge length one) for a fixed price \alpha. Instead, we assume that quality levels (i.e., edge lengths) are varying in a fixed interval [\beta,B], 0 < \beta <= B. A node now cannot only choose which edge to buy, but can also choose its quality x, for the price p(x), for a given price function p. For both games and all price functions, we show that Nash equilibria exist and that the price of stability is either constant or depends only on the interval size of available edge lengths. Our main results are bounds for the price of anarchy. In case of the SUM-game, we show that they are tight if price functions decrease sufficiently fast.Comment: An extended abstract of this paper has been accepted for publication in the proceedings of the 10th International Conference on Web and Internet Economics (WINE

A Step towards Explainable Artificial Neural Networks in Image Processing by Dataset Assessment

Artificial neural networks, image processing, premodeling explainability, robot vision system

Relating Planner Task Performance for Container Terminal Operations to Multi-Tasking Skills and Personality Type

Planning the operations within a container terminal is a complex task. It requires planners to demonstrate adaptive behavior while handling stressful, complex, and unexpected situations in today’s dynamic and technology dependent workplace. This paper aims at investigating the role of multi-tasking ability, moderated by an individual’s personality type, in predicting planner task performance using simulation gaming methods. Hierarchical regression analysis results demonstrate that the direct effect of multi-tasking ability on performance is positive and significant. With one exception, the personality traits do not significantly intensify or lessen the impact of multi-tasking in predicting task performance. The personality trait, openness to experience, significantly lessens the impact of multi-tasking ability on performance. Our results suggest that container terminal operators may benefit by considering the above-mentioned results while allocating planning tasks to their employees and new recruits. The instruments used in this research could also be used for evaluating and training candidate planners