Fingerstroke time estimates for touchscreen-based mobile gaming interaction

The growing popularity of gaming applications and ever-faster mobile carrier networks have called attention to an intriguing issue that is closely related to command input performance. A challenging mirroring game service, which simultaneously provides game service to both PC and mobile phone users, allows them to play games against each other with very different control interfaces. Thus, for efficient mobile game design, it is essential to apply a new predictive model for measuring how potential touch input compares to the PC interfaces. The present study empirically tests the keystroke-level model (KLM) for predicting the time performance of basic interaction controls on the touch-sensitive smartphone interface (i.e., tapping, pointing, dragging, and flicking). A modified KLM, tentatively called the fingerstroke-level model (FLM), is proposed using time estimates on regression models.     

Notes on ‘Bemächtigungstrieb’ and Strachey’s translation as ‘instinct for mastery’

This short paper looks at Freud’s use of the term ‘Bemächtigungstrieb’ and its translation by Strachey as ‘instinct for mastery’ when Freud was describing the motives behind his grandson’s game with the wooden reel and string in Beyond the Pleasure Principle. The word ‘Macht’ [power], which is contained in the word ‘Bemächtigung’ points to Freud’s difficult relationship with Alfred Adler, whose early theories on the aggressive drive and later theories on ‘striving for power’ were initially rejected by Freud. Looking at the changes in Freud’s reception of Adlerian terms, some of which he later integrated into his own theory, throws light on his choice of the word ‘Bemächtigungstrieb’ in 1920, when he was just beginning to introduce his thoughts on the death instinct. A slightly different translation of the word ‘Bemächtigungstrieb’, one which takes these historical and theoretical aspects into account, could make these connections clearer for the English reader.     

Impaired social learning in patients with major depressive disorder revealed by a reinforcement learning model

Background/objectivePatients with major depressive disorder (MDD) have altered learning rates for rewards and losses in non-social learning paradigms. However, it is not well understood whether the ability to learn from social interactions is altered in MDD patients. Using reinforcement learning during the repeated Trust Game (rTG), we investigated how MDD patients learn to trust newly-met partners in MDD patients.MethodSixty-eight MDD patients and fifty-four controls each played as ‘investor’ and interacted with ten different partners. We manipulated both the level of trustworthiness by varying the chance of reciprocity (10, 30, 50, 70 and 90%) and reputation disclosure, where partners’ reputation was either pre-disclosed or hidden.ResultsOur reinforcement learning model revealed that MDD patients had significantly higher learning rates for losses than the controls in both the reputation disclosure and non-disclosure condition. The difference was larger when reputation was not disclosed than disclosed. We observed no difference in learning rates for gains in either condition.ConclusionsOur findings highlight that abnormal learning for losses underlies the social learning process in MDD patients. This abnormality is higher when situational unpredictability is high versus low. Our findings provide novel insights into social rehabilitation of MDD.     

Model and interactive algorithm of bi‐level multi‐objective decision‐making with multiple interconnected decision makers

Furthering a prior research on two‐person bi‐level multi‐objective decision‐making problems of the leader‐follower Stackelberg game, we present an extended model of bi‐level multi‐objective decision‐making with multiple interconnected decision makers at the lower level. In the model, the upper level decision maker acts as a leader and the lower level decision makers behave as the followers, and inter‐connections and interactions exist among these followers in decision‐making scenarios. Following the rules of leader‐follower Stackelberg game, we develop an interactive algorithm of the model for solving multi‐objective decision‐making problems and reflecting the interactive natures among the decision makers. Finally, the authors exemplify the model and algorithm, and draw a conclusion on points of contributions and the significance of this study in decision‐making and support. Copyright © 2001 John Wiley & Sons, Ltd.     

两人问题解决中惯例的测量及其微观发生过程

惯例是一种群体的程序化行为，类似于思维定势，其实验测量最早源于 Cohen 与 Bacdayan (1994)发明的TTT扑克牌游戏。研究选取35对两人组被试，在问题解决的框架下采用微观发生法的思路重新设计实验任务，探讨了两人问题解决中惯例的表现，并在此基础上探讨了惯例从无到有的产生过程。结果表明：(1)修改后的40局TTT扑克牌游戏中存在明显的惯例现象，这可以从可靠性、速度、重复的行动序列、基于特定策略的行为模式和偶尔的次优性5个指标进行验证和描述。(2)惯例的产生是在行为掌握基础上，不断进行表征重述的结果。这一过程体现了惯例的产生是程序性知识转向陈述性知识、无意识转向有意识、稳定性与可变性的统一。