Tailored gamification and serious game framework based on fuzzy logic for saving energy in connected thermostats

Connected thermostats (CTs) often save less energy than predicted because consumers may not know how to use them and may not be engaged in saving energy. Additionally, several models perform contrary to consumers’ expectations and are thus not used the way they are intended to. As a result, CTs save less energy and are underused in households. This paper reviews aspects of gamification and serious games focused on engaging consumers. A gamification and serious games framework is proposed for saving energy that is tailored by a fuzzy logic system to motivate connected thermostat consumers. This intelligent gamification framework can be used to customize the gamification and serious game strategy to each consumer so that fuzzy logic systems can be adapted according to the requirements of each consumer. The framework is designed to teach, engage, and motivate consumers while helping them save electrical energy when using their thermostats. It is described the proposed framework as well as a mockup that can be run on a cellphone. Although this framework is designed to be implemented in CTs, it can be translated to their energy devices in smart homes

The impact of peoples' personal dispositions and personalities on their trust of robots in an emergency scenario

Humans should be able to trust that they can safely interact with their home companion robot. However, robots can exhibit occasional mechanical, programming or functional errors. We hypothesise that the severity of the consequences and the timing of a robot's different types of erroneous behaviours during an interaction may have different impacts on users' attitudes towards a domestic robot. First, we investigated human users' perceptions of the severity of various categories of potential errors that are likely to be exhibited by a domestic robot. Second, we used an interactive storyboard to evaluate participants' degree of trust in the robot after it performed tasks either correctly, or with 'small' or 'big' errors. Finally, we analysed the correlation between participants' responses regarding their personality, predisposition to trust other humans, their perceptions of robots, and their interaction with the robot. We conclude that there is correlation between the magnitude of an error performed by a robot and the corresponding loss of trust by the human towards the robot. Moreover we observed that some traits of participants' personalities (conscientiousness and agreeableness) and their disposition of trusting other humans (benevolence) significantly increased their tendency to trust a robot more during an emergency scenario.Peer reviewe

Negotiating over mobile phones: calling or being called can make the difference

Mobile phones pervade our everyday life like no other technology, but the effects they have on one-to-one conversations are still relatively unknown. This paper focuses on how mobile phones influence negotiations, i.e., on discussions where two parties try to reach an agreement starting from opposing preferences. The experiments involve 60 pairs of unacquainted individuals (120 subjects). They must make a “yes” or “no” decision on whether several objects increase the chances of survival in a polar environment or not. When the participants disagree about a given object (one says “yes” and the other says “no”), they must try to convince one another and reach a common decision. Since the subjects discuss via phone, one of them (selected randomly) calls while the other is called. The results show that the caller convinces the receiver in 70 % of the cases ( p value = 0.005 according to a two-tailed binomial test). Gender, age, personality and conflict handling style, measured during the experiment, fail in explaining such a persuasiveness difference. Calling or being called appears to be the most important factor behind the observed result

Drivers’ behaviour modelling for virtual worlds

In this paper we present a study that looks at modelling drivers’ behaviour with a view to contribute to the problem of road rage. The approach we adopt is based on agent technology, particularly multi-agent systems. Each driver is represented by a software agent. A virtual environment is used to simulate drivers’ behaviour, thus enabling us to observe the conditions leading to road rage. The simulated model is then used to suggest possible ways of alleviating this societal problem. Our agents are equipped with an emotional module which will make their behaviours more human-like. For this, we propose a computational emotion model based on the OCC model and probabilistic cognitive maps. The key influencing factors that are included in the model are personality, emotions and some social/personal attributes

Employee Screening : Theory and Evidence

Arguably the fundamental problem faced by employers is how to elicit effort from employees. Most models suggest that employers meet this challenge by monitoring employees carefully to prevent shirking. But there is another option that relies on heterogeneity across employees, and that is to screen job candidates to find workers with a stronger work ethic who require less monitoring. This should be especially useful in work systems where monitoring by supervisors is more difficult, such as teamwork systems. We analyze the relationship between screening and monitoring in the context of a principal-agent model and test the theoretical results using a national sample of U.S. establishments, which includes information on employee selection. We find that employers screen applicants more intensively for work ethic where they make greater use of systems such as teamwork where monitoring is more difficult. This screening is also associated with higher wages, as predicted by the theory : The synergies between reduced monitoring costs and high performance work systems enable the firm to pay higher wages to attract and retain such workers. Screening for other attributes, such as work experiences and academic performance, does not produce these results.Employee Screening, Monitoring, Work Ethic, High Performance Work Practices, Principal-Agent Model

Personality Psychology and Economics

This paper explores the power of personality traits both as predictors and as causes of academic and economic success, health, and criminal activity. Measured personality is interpreted as a construct derived from an economic model of preferences, constraints, and information. Evidence is reviewed about the "situational specificity" of personality traits and preferences. An extreme version of the situationist view claims that there are no stable personality traits or preference parameters that persons carry across different situations. Those who hold this view claim that personality psychology has little relevance for economics. The biological and evolutionary origins of personality traits are explored. Personality measurement systems and relationships among the measures used by psychologists are examined. The predictive power of personality measures is compared with the predictive power of measures of cognition captured by IQ and achievement tests. For many outcomes, personality measures are just as predictive as cognitive measures, even after controlling for family background and cognition. Moreover, standard measures of cognition are heavily influenced by personality traits and incentives. Measured personality traits are positively correlated over the life cycle. However, they are not fixed and can be altered by experience and investment. Intervention studies, along with studies in biology and neuroscience, establish a causal basis for the observed effect of personality traits on economic and social outcomes. Personality traits are more malleable over the life cycle compared to cognition, which becomes highly rank stable around age 10. Interventions that change personality are promising avenues for addressing poverty and disadvantage.personality, behavioral economics, cognitive traits, wages, economic success, human development, person-situation debate

Employee Screening: Theory and Evidence

Arguably the fundamental problem faced by employers is how to elicit effort from employees. Most models suggest that employers meet this challenge by monitoring employees carefully to prevent shirking. But there is another option that relies on heterogeneity across employees, and that is to screen job candidates to find workers with a stronger work ethic who require less monitoring. This should be especially useful in work systems where monitoring by supervisors is more difficult, such as teamwork systems. We analyze the relationship between screening and monitoring in the context of a principal-agent model and test the theoretical results using a national sample of U.S. establishments, which includes information on employee selection. We find that employers screen applicants more intensively for work ethic where they make greater use of systems such as teamwork where monitoring is more difficult. This screening is also associated with higher wages, as predicted by the theory: The synergies between reduced monitoring costs and high performance work systems enable the firm to pay higher wages to attract and retain such workers. Screening for other attributes, such as work experiences and academic performance, does not produce these results.Employee Screening, Monitoring, Work Ethic, High Performance Work Practices, Principal-Agent Model.

Towards Learning ‘Self’ and Emotional Knowledge in Social and Cultural Human-Agent Interactions

Original article can be found at: http://www.igi-global.com/articles/details.asp?ID=35052 Copyright IGI. Posted by permission of the publisher.This article presents research towards the development of a virtual learning environment (VLE) inhabited by intelligent virtual agents (IVAs) and modeling a scenario of inter-cultural interactions. The ultimate aim of this VLE is to allow users to reflect upon and learn about intercultural communication and collaboration. Rather than predefining the interactions among the virtual agents and scripting the possible interactions afforded by this environment, we pursue a bottomup approach whereby inter-cultural communication emerges from interactions with and among autonomous agents and the user(s). The intelligent virtual agents that are inhabiting this environment are expected to be able to broaden their knowledge about the world and other agents, which may be of different cultural backgrounds, through interactions. This work is part of a collaborative effort within a European research project called eCIRCUS. Specifically, this article focuses on our continuing research concerned with emotional knowledge learning in autobiographic social agents.Peer reviewe