Artificial consciousness, artificial emotions, and autonomous robots

Nowadays for robots, the notion of behavior is reduced to a simple factual concept at the level of the movements. On another hand, consciousness is a very cultural concept, founding the main property of human beings, according to themselves. We propose to develop a computable transposition of the consciousness concepts into artificial brains, able to express emotions and consciousness facts. The production of such artificial brains allows the intentional and really adaptive behavior for the autonomous robots. Such a system managing the robot’s behavior will be made of two parts: the first one computes and generates, in a constructivist manner, a representation for the robot moving in its environment, and using symbols and concepts. The other part achieves the representation of the previous one using morphologies in a dynamic geometrical way. The robot’s body will be seen for itself as the morphologic apprehension of its material substrata. The model goes strictly by the notion of massive multi-agent’s organizations with a morphologic control.     

Intuitive control of mobile robots: an architecture for autonomous adaptive dynamic behaviour integration

In this paper, we present a novel approach to human–robot control. Taking inspiration from behaviour-based robotics and self-organisation principles, we present an interfacing mechanism, with the ability to adapt both towards the user and the robotic morphology. The aim is for a transparent mechanism connecting user and robot, allowing for a seamless integration of control signals and robot behaviours. Instead of the user adapting to the interface and control paradigm, the proposed architecture allows the user to shape the control motifs in their way of preference, moving away from the case where the user has to read and understand an operation manual, or it has to learn to operate a specific device. Starting from a tabula rasa basis, the architecture is able to identify control patterns (behaviours) for the given robotic morphology and successfully merge them with control signals from the user, regardless of the input device used. The structural components of the interface are presented and assessed both individually and as a whole. Inherent properties of the architecture are presented and explained. At the same time, emergent properties are presented and investigated. As a whole, this paradigm of control is found to highlight the potential for a change in the paradigm of robotic control, and a new level in the taxonomy of human in the loop systems.     

Change schools through revolution,not evolution

The school's traditional practices are linked to current failures and to the limited prospects of future success. The major problems with current school practices are: adopting instructional programs that have never been fieldtested and revised on the basis of data; using diagnostic practices that blame the child as being the sole cause of poor performance; using testing techniques that do not imply curricular remedies; promoting children beyond their grade-level performance; failing to provide teachers with effective training and monitoring. Recommendations for changing the system to become accountable and databased include: bringing pressure from outside the system; lobbying for alternatives to public schools; promoting intervention by the board; involving parents in union negotiations; establishing committees of expert teachers to review administrative proposals and report to the board. The central feature of the plan is to fire administrators who fail to meet attainable student-achievement goals. This practice would ensure that administrators are reinforced when children succeed, a feature that is not part of current practices.     

Intrinsic goals for leisure-time physical activity predict children's daily step counts through autonomous motivation

ObjectivesThe present study tested a motivational sequence in which children's goals for leisure-time sport and physical activity (PA) from Goal Content Theory predicted pedometer-determined PA through behavioural regulation constructs from Self-Determination Theory.DesignQuantitative cross-sectional study.MethodsA sample of 1272 Flemish (Dutch speaking part of Belgium) sixth graders (M age = 11.42 years) filled in a questionnaire on PA goal content, behavioural regulations and pubertal status. Children's height and weight were measured to assess Body Mass Index (BMI). To measure daily PA behaviour, participants wore a pedometer for seven consecutive days. Structural equation modelling was performed to test the proposed motivational sequence and to examine the mediation effect of behavioural regulations towards leisure-time sport and PA on the relation between PA goal content and daily step counts.ResultsA structural equation model supported the hypothesized sequence in which intrinsic goals for leisure-time sport and PA predicted children's daily step counts through autonomous motivation towards leisure-time sport and PA. Multi-sample invariance testing revealed that the proposed model was largely invariant across BMI groups, pubertal status and gender.ConclusionsThe findings highlight the importance of emphasizing intrinsic goals for participation in leisure-time sport and PA in children aged 10–12 years. By stimulating children to participate in PA and sports by referring to intrinsic goals, children are more likely to enjoy PA, which in turn might increase the likelihood of a regular and long-term PA engagement.     

Synthesis of theories through parametrisation of laws

The paper presents an example of unified theory bearing interest from both a historical and systematic point of view. The example is chosen from evolutionary population genetics (neo-Darwinian synthetic theory). It exhibits various aspects of theoretical change in science that have been shown in Part I (Geiger, 1988) to be characteristic of syntheses of theories.     

Investigating driver reactions to movements of autonomous vehicle in permitted right turn through driving simulator experiments

Traffic safety has always been a hot topic for human-driven (HDV) and autonomous vehicles (AV) mixed flow. The conflict between permitted right-turn vehicles (PRT) and opposing through vehicles (TH) at signalized intersections (left-handed traffic) is extraordinarily critical. AVs with aggressive behaviors are able to accept short gap time without losing safety. However, such a turning maneuver may lead to dangerous feelings and cause unexpected reactions of approaching drivers. This study aims to investigate and model drivers’ reactions in TH movements to PRT AVs considering the trust degree of drivers to AVs. Questionnaire surveys and driving simulator experiments were conducted for 41 participants. Results reveal that the right turn timing of PRT AV will significantly influence drivers’ reactions. Basically, TH drivers will brake with a high probability under the situation of small expected post encroachment time (PET). It is also found that female drivers and drivers with low trust in AVs are more vigilant to PRT AVs than other drivers. Based on this finding a two-layer model for reproducing TH drivers’ reactions to PRT AVs is proposed. The first layer is to determine the braking decision and the second layer is to calculate the parameters of braking behaviors (brake lag, braking time, and speed drop). The significance and coefficients variables in these models proved that the trust in AV will influence drivers’ decisions and braking behaviors (brake lag and braking time). The more the drivers trust AVs, the smaller the expected PET to AVs they can accept for passing without braking, and the more gently they will brake (longer brake lag and shorter braking time) due to the cutting in of PRT AVs. This effect will become significant after drivers have experienced several interactions with AVs.     

Beyond the image paradigm: Systemic evolution through participative planning

This paper is an attempt at introducing a formal framework for societal, participative, anticipatory, inner‐change oriented and open‐ended ‘’ learning for evolution.” The key point of our approach is that it considers the evolution of a social system not exclusively as an appropriate result of the given system structure, operating and behaving under external constraints; but mainly as an outer (or observable) consequence of some inner changes brought about from within the system of heterogenous actors‐designers in their effort to cope with complexities generated equally by external constraints and by the network of mutual relationships between them. The actors‐designers are thus trying to assess critically the courses the system could possibly take in the future and also to isolate —through a dialogue between them—the so‐called “evolutionary” ones. Consequently, a policy‐oriented approach to “social homcorhesis” is obtained. It opens the way to a participative planning outlook on societal learning.     

Making sense of social robots: A structural analysis of the layperson's social representation of robots

IntroductionGiven their novelty, social robots (i.e., robots using natural language, displaying and recognizing emotions) will generate uncertainty among users. Social representations allow making sense of the new, drawing from existing knowledge.ObjectiveA free association questionnaire was administered to 212 Portuguese adults to identify the social representation of robot.MethodData was analysed with EVOC 2000 and SIMI 2000 software.ResultsThe social representation of robot is organized around the ideas of technology, help and future. Differences in the representation according to age, gender and level of education where also identified.ConclusionThe social representation of robot is marked by the conception of it as a tool. This contrasts with the concept of social robots as social agents. Implications for social robot's acceptance are discussed.     

Moral psychology of nursing robots: Exploring the role of robots in dilemmas of patient autonomy

Artificial intelligences (AIs) are widely used in tasks ranging from transportation to healthcare and military, but it is not yet known how people prefer them to act in ethically difficult situations. In five studies (an anthropological field study, n = 30, and four experiments, total n = 2150), we presented people with vignettes where a human or an advanced robot nurse is ordered by a doctor to forcefully medicate an unwilling patient. Participants were more accepting of a human nurse's than a robot nurse's forceful medication of the patient, and more accepting of (human or robot) nurses who respected patient autonomy rather than those that followed the orders to forcefully medicate (Study 2). The findings were robust against the perceived competence of the robot (Study 3), moral luck (whether the patient lived or died afterwards; Study 4), and command chain effects (Study 5; fully automated supervision or not). Thus, people prefer robots capable of disobeying orders in favour of abstract moral principles like valuing personal autonomy. Our studies fit in a new era in research, where moral psychological phenomena no longer reflect only interactions between people, but between people and autonomous AIs.     

Education biases perception of social robots

IntroductionRecent research on human–robot interactions (HRI) emphasizes a role of user's attitudes in perceiving robot's with different robot embodiments of varying levels of human likenesses. However, other human factors such as educational background may also help understanding of what conditions contribute to enhance social perception of robot's features.ObjectivesThis study aimed to determine how people's attitudes towards and familiarization with robots influence social perception of particular features of robots.MethodFirst, we measured attitudes towards robots among undergraduate students with diverse educational background (engineering vs. psychology). Then, participants were presented with short movies showing the behaviour of three robots with different levels of sociability. Finally, participants evaluated the characteristics of these robots on a scale.ResultsPeople more familiar with social robots and with more positive attitudes towards them evaluate robots with human traits more highly.ConclusionHuman perception of social robots resembles social phenomena related to human perception of other people.     

Evolving grounded communication for robots

The computational and robotic synthesis of language evolution is emerging as a new exciting field of research. The objective is to come up with precise operational models of how communities of agents, equipped with a cognitive apparatus, a sensori-motor system, and a body, can arrive at shared grounded communication systems. Such systems may have similar characteristics to animal communication or human language. Apart from its technological interest in building novel applications in the domain of human-robot or robot-robot interaction, this research is of interest to the many disciplines concerned with the origins and evolution of language and communication.     

Unveiling the reasoning processes of robots through introspective dialogues in a storytelling system: A study on the elicited empathy

The work studies the empathy elicited by a storytelling system in which the characters in the story are interpreted by humanoid robots and modelled as cognitive agents. The ACT-R architecture is exploited to shape the characters’ personalities and equip them with knowledge and behaviours typical of social practices. The narration is enriched with gestures and emotional expressions obtained by setting parameters that can be correlated to some emotions, such as the pitch and speech rate, the LEDs colour and the head inclination. The system has been evaluated by comparing a simple narrative modality with an enhanced one, where an introspective dialogue is adopted to explain and let transparent the internal reasoning processes of the characters. The obtained results show that storytelling affected the cognitive component of empathy, especially through the advanced narrative mode.     

Remote control and children's understanding of robots

Children use goal-directed motion to classify agents as living things from early in infancy. In the current study, we asked whether preschoolers are flexible in their application of this criterion by introducing them to robots that engaged in goal-directed motion. In one case the robot appeared to move fully autonomously, and in the other case it was controlled by a remote. We found that 4- and 5-year-olds attributed fewer living thing properties to the robot after seeing it controlled by a remote, suggesting that they are flexible in their application of the goal-directed motion criterion in the face of conflicting evidence of living thing status. Children can flexibly incorporate internal causes for an agent’s behavior to enrich their understanding of novel agents.     

Using robots to understand animal cognition

In recent years, robotic animals and humans have been used to answer a variety of questions related to behavior. In the case of animal behavior, these efforts have largely been in the field of behavioral ecology. They have proved to be a useful tool for this enterprise as they allow the presentation of naturalistic social stimuli whilst providing the experimenter with full control of the stimulus. In interactive experiments, the behavior of robots can be controlled in a manner that is impossible with real animals, making them ideal instruments for the study of social stimuli in animals. This paper provides an overview of the current state of the field and considers the impact that the use of robots could have on fundamental questions related to comparative psychology: namely, perception, spatial cognition, social cognition, and early cognitive development. We make the case that the use of robots to investigate these key areas could have an important impact on the field of animal cognition.     

Contextual factors in the appearance of consumer robots: exploratory assessment of perceived anxiety toward humanlike consumer robots.

The authors use the "uncanny valley theory" as a diagnostic lens to better understand consumers' perceptions of humanlike consumer robots in different contexts. The results demonstrate that individuals were indifferent about the extent of the humanness of robotic images in the context of touching the robots. However, respondents showed more concern for robotic images' similarity to humans in the contexts of communicating with robots, watching robots in a movie, and living in the same house with robots. One key contribution of the study includes the initial empirical foundation for understanding individual evaluation of the appearance of consumer robots in a variety of contexts.