Thiago Medeiros de Menezes, Sidia, Manaus, Brazil
Evaluating the User Experience in some contexts is challenging, especially in automation applications, due to specific situations and requirements. This paper presents an experience of applying the UX evaluation method for an automation tool in the Android software industry to assist software engineers in identifying the UX problems faced by users. The work applies heuristic evaluation, survey, and user interview methods to find the UX problems, understand the respective reasons, validate the given information, and finally assess the UX. The evaluation identified critical problems related to error messages, system response to errors, and proper feedback about what software is doing. The found problems and discussions contributed to developing new UX evaluation methodologies.
UX Assessment, UX Evaluation, User Experience, UX.
Zhiqiang Gou1, Yujia Zhang2, Xinyue Li2 and Ya Li*1, 1School of Computer and Information Science, Southwest University, Chongqing, China, 2School of Hanhong, Southwest University, Chongqing, China
Evolutionary game theory provides a good and comprehensive framework for studying the evolution of cooperation. In many dilemmas, decisions are determined not by a single factor, but by multiple factors, including memory, reputation, reward and punishment. Cooperative evolutionary behavior based on memory mechanism has become a hot topic in recent years. However, most previous studies have considered historical returns when individuals choose the role they will learn from, but have focused less on the stability of strategies. Based on the characteristics of historical strategy information, a new strategy update rule is proposed to study the influence of the stability of historical strategy information on the evolution of cooperation in spatial prisoner's dilemma games, and the influence of memory weight on cooperation is also considered. The level of strategy stability is measured by the number of times that the strategies in the memory length are continuous and consistent with the current strategy. It can determine the probability of individuals learning neighbor strategies when updating strategies. The numerical simulation results show that in steady state, the memory length has a great influence on the level of cooperation. The greater the memory length, the higher stability of the strategy, and the more conducive to the emergence and dynamic evolution of cooperation. The stability strategy update mechanism has proposed in terms of memory length can improve network reciprocity. Limited memory enables us to design effective mechanisms to promote cooperation and help to further understand the origin of cooperation in social and biological systems.
Evolutionary game theory, Historical strategy, Prisoner's dilemma, Square lattice.