Violent video game play impacts facial emotion recognition

This study assessed the speed of recognition of facial emotional expressions (happy and angry) as a function of violent video game play. Color photos of calm facial expressions morphed to either an angry or a happy facial expression. Participants were asked to make a speeded identification of the emotion (happiness or anger) during the morph. Typically, happy faces are identified faster than angry faces (the happy-face advantage). Results indicated that playing a violent video game led to a reduction in the happy face advantage. Implications of these findings are discussed with respect to the current models of aggressive behavior.     

合作数学问题解决与心理模型建构关系研究

合作学习研究者很早就开始关注合作互动中解释的作用。Chi关于自我解释的研究表明解释是一种非常有效果的学习现象,能够起到修补和建立学习者的心理模型的作用。本研究以28名高一学生为被试,采取了两种程序的合作学习任务,研究中虽然没有发现两种程序在问题解决结果上的显著差异,但是却表现出在心理模型建构方面互动效果上的差异,或表现为同等效果下的互动次数有显著性差异。     

Situated language understanding as filtering perceived affordances

We introduce a computational theory of situated language understanding in which the meaning of words and utterances depends on the physical environment and the goals and plans of communication partners. According to the theory, concepts that ground linguistic meaning are neither internal nor external to language users, but instead span the objective-subjective boundary. To model the possible interactions between subject and object, the theory relies on the notion of perceived affordances: structured units of interaction that can be used for prediction at multiple levels of abstraction. Language understanding is treated as a process of filtering perceived affordances. The theory accounts for many aspects of the situated nature of human language use and provides a unified solution to a number of demands on any theory of language understanding including conceptual combination, prototypicality effects, and the generative nature of lexical items. To support the theory, we describe an implemented system that understands verbal commands situated in a virtual gaming environment. The implementation uses probabilistic hierarchical plan recognition to generate perceived affordances. The system has been evaluated on its ability to correctly interpret free-form spontaneous verbal commands recorded from unrehearsed game play between human players. The system is able to "step into the shoes" of human players and correctly respond to a broad range of verbal commands in which linguistic meaning depends on social and physical context. We quantitatively compare the system's predictions in response to direct player commands with the actions taken by human players and show generalization to unseen data across a range of situations and verbal constructions.     

The Others Will Help: The Presence of Multiple Video Game Characters Reduces Helping After the Game Is Over

The bystander effect refers to the phenomenon that individuals are less likely to help if there are potential other helpers present. For instance, past research revealed that participants were less likely to help computer-controlled characters if there were other computer-controlled characters present. Research has also shown that the bystander effect occurs if the presence of others is merely imagined. The present research examined the idea that the presence of multiple characters within a video game reduces the player's helping behavior even after the video game is over. In fact, participants who played a video game with multiple characters present were less likely to devote time to assisting in a future study than participants who had played the same video game with only a single character present.     

Everyday sadism predicts violent video game preferences

Playing violent video games has become an integral part of the lives of many people, although some people more than others may be predisposed to enjoy violent video games. Two cross-sectional studies examined the extent to which everyday sadism predicts the amount of violent video game play. Past research has shown that everyday sadists obtain pleasure from cruel behaviors. Hence, I reasoned that everyday sadists are drawn to violent video games because killing game characters might be an opportunity to satisfy their need for cruelty. In fact, results revealed a positive link between everyday sadism and the amount of violent video game exposure. Moreover, this relation statistically held when controlling for the impact of trait aggression, the Big 5, narcissism, Machiavellianism, and psychopathy.     

Changes in cooperative behaviour and belief in finitely repeated social dilemmas

Economic and psychological studies have determined the tendency to improve cooperation in initial interactions in which people are required to contribute in public good games. The current study examined the behavioural changes of individuals during finite interaction times. Participants were invited to make decisions twice in a step‐level public good game, and their belief in achieving the collective interest was measured. Participants were divided into three groups based on their first decisions. Results showed that high contributors demonstrated high levels of contribution in their subsequent interactions, whereas low and equal contributors increased their levels of contribution after the initial interaction. Additionally, the cooperative level of low contributors increased along with their cooperative belief. The theoretical and practical implications of changes of behaviour and belief in repeated social dilemmas were identified.     

人际控制感对合作行为的影响:一项囚徒困境的ERPs研究

社会困境中的合作行为是通过抑制个体利益最大化的诱惑从而满足集体利益最大化的过程。研究采用囚徒困境游戏范式考察个体的合作行为,通过设置决策顺序操控人际控制感的高低,利用ERPs技术探讨了人际控制感影响合作行为的神经机制。行为结果发现:高人际控制感条件下个体做出合作行为的频率显著高于低人际控制感。ERPs结果发现:个体在高人际控制感条件下博弈时顶枕区所诱发的P2波幅更小,且右侧额区所诱发的N2波幅也更小。这表明被试在高人际控制感条件下感知到的不确定性更小,冲突控制水平更高,从而更能抑制利己诱惑,表现出更多的合作行为。     

THE MODERN INVENTION OF “SCIENCE‐AND‐RELIGION”: WHAT FOLLOWS?

I am grateful to the four reviewers of The Territories of Science and Religion for their careful and insightful readings of the book, and their kind words about it. They all got the central arguments pretty much right, and thus any critical comments are not the result of fundamental misunderstandings. While there are some common themes in the assessments, each reviewer, happily, has offered a distinct perspective on the book. For this reason I will deal with their comments in turn, but with a focus throughout on a generally expressed concern about the broader implications of the book's historical analysis, and what positive or concrete proposals might follow from it.     

When to (or not to) trust intelligent machines: Insights from an evolutionary game theory analysis of trust in repeated games

The actions of intelligent agents, such as chatbots, recommender systems, and virtual assistants are typically not fully transparent to the user. Consequently, users take the risk that such agents act in ways opposed to the users’ preferences or goals. It is often argued that people use trust as a cognitive shortcut to reduce the complexity of such interactions. Here we formalise this by using the methods of evolutionary game theory to study the viability of trust-based strategies in repeated games. These are reciprocal strategies that cooperate as long as the other player is observed to be cooperating. Unlike classic reciprocal strategies, once mutual cooperation has been observed for a threshold number of rounds they stop checking their co-player’s behaviour every round, and instead only check it with some probability. By doing so, they reduce the opportunity cost of verifying whether the action of their co-player was actually cooperative. We demonstrate that these trust-based strategies can outcompete strategies that are always conditional, such as Tit-for-Tat, when the opportunity cost is non-negligible. We argue that this cost is likely to be greater when the interaction is between people and intelligent agents, because of the reduced transparency of the agent. Consequently, we expect people to use trust-based strategies more frequently in interactions with intelligent agents. Our results provide new, important insights into the design of mechanisms for facilitating interactions between humans and intelligent agents, where trust is an essential factor.