Socially emotional brain-inspired cognitive architecture framework for artificial intelligence

Artificial Intelligence of the next generation needs to interact with users socially, convincing them in its ability to understand human minds, including emotions. For this to happen, an artificial emotional intelligence is needed, capable of adequate, believable behavior in social emotional interactions. Building on previous developments, the present work extends the general framework of emotional Biologically Inspired Cognitive Architecture (eBICA: Samsonovich, 2013, 2018), endowing it with fluents describing, in addition to appraisals, somatic markers, feelings, emotions, moods, emotional reactions and biases. Key building blocks that integrate them are moral schemas and semantic maps. The model describes interaction of three factors: plans and commitments, moral and ethical values, and somatic comfort. Learning in this framework includes self-organization of semantic maps that in turn may provide guidance for active humanlike learning. Implications for empirical studies and practical applications are discussed together with the expected impact.     

The affective interval: An investigation of the peaks and valleys during high- and moderate-intensity interval exercise in regular exercisers

Evidence supports the notion that people generally feel worse during high(er) intensity exercise but experience an affective rebound immediately following cessation that often exceeds pre-exercise feeling states. Considering rest/recovery is an integral part of interval exercise, it is of interest to determine the degree of affective reactivity and recovery that may occur during interval exercise of different intensities. The purpose of the present study was to examine affective reactivity to and recovery from an acute bout of moderate-intensity (MIIE) and high-intensity interval exercise (HIIE). Participants (N = 25, 13 females, 23.3 ± 4.0 yrs, BMI = 25.7 ± 4.1 kg m⁻²) completed 4 sessions at the same time of day with at least 24-h between each session: a baseline session to record resting affect, a graded exercise test on a stationary bike (cycle ramp protocol 25 W·min-1) to volitional exhaustion, and then completed a high- (HIIE) and moderate-intensity interval exercise (MIIE) session where affect was recorded prior to, during, and up to 30-min post exercise. Participants reported more negative feeling states during the HIIE session compared to the MIIE session, but these states recovered similarly as early as 5-min post-exercise. In addition, while affective change (reactivity and rebounds) were relatively equal during the MIIE, declines in affect during the HIIE outweighed the affective rebounds associated with rest, resulting in a large decline in affective state from pre-exercise.     

Idiographic network analysis of discrete mood states prior to treatment

Idiographic network models based on time‐series data have received recent attention for their ability to model relationships among symptoms and behaviours as they unfold in time within a single individual (cf. Epskamp, Borsboom, & Fried, 2018; Fisher, Medaglia, & Jeronimus, 2018). Rather than examine the correlational relationships between variables in a sample of individuals, an idiographic network examines correlations within a single person, averaged over many time points. Because the approach averages over time, the data must be stationary (i.e. relatively consistent over time). If individuals experience varying states over time—different mixtures of symptoms and behaviours in one moment or another—then averaging over categorically different moments may undermine model accuracy. Fisher and Bosley (2019) address these concerns via the application of Gaussian finite mixture modelling to identify latent classes of time points in intraindividual time‐series data from a sample of adults with major depressive disorder and/or generalised anxiety disorder (n = 45). The present paper outlines an extension of this work, wherein network analysis is used to model within‐class covariation of symptoms. To illustrate this approach, network models were constructed for each intraindividual class identified by Fisher and Bosley (137 networks across the 45 participants, mean classes/person = ~3, range = 2–4 classes/person). We examine the relative consistency in symptom organisation between each individual's multiple mood state networks and assess emergent group‐level patterns. We highlight opportunities for enhanced treatment personalisation and review nomothetic patterns relevant to transdiagnostic conceptualisations of psychopathology. We address opportunities for integrating this approach into clinical practice and outline potential shortcomings.     

The perception of preschool social dominance

Children's and teachers' perception of social dominance was examined using a behavioral criterion for determining accuracy of verbal judgments. Video records of agonistic interactions were obtained during approximately 60 hours of free-play at two preschool centers. Analyses of social conflict episodes ending in submission revealed linear dominance structures for both groups. Dominance perception was assessed in two ways. Both teachers and children were asked to rank-order a subgroup of children according to dominance. They were also asked to select the more dominant children in a number of predetermined pairs. Results indicated that teachers could accurately judge dyadic dominance relations, and that accuracy among children varied as a function of their status within the group hierarchy. Findings have implications for social dominance assessment methodology, and for the issue of consensual versus ecological validity in developmental studies of social perception.     

A tuned-trace theory of interval-timing dynamics

Animals on interval schedules of reinforcement can rapidly adjust a temporal dependent variable, such as wait time, to changes in the prevailing interreinforcement interval. We describe data on the effects of impulse, step, sine-cyclic, and variable-interval schedules and show that they can be explained by a tuned-trace timing model with a one-back threshold-setting rule. The model can also explain steady-state timing properties such as proportional and Weber law timing and the effects of reinforcement magnitude. The model assumes that food reinforcers and other time markers have a decaying effect (trace) with properties that can be derived from the rate-sensitive property of habituation (the multiple-time-scale model). In timing experiments, response threshold is determined by the trace value at the time of the most recent reinforcement. The model provides a partial account for the learning of multiple intervals, but does not account for scalloping and other postpause features of responding on interval schedules and has some problems with square-wave schedules.     

2001 DIVISION 27 PRESIDENTIAL ADDRESS: Emotional Intelligence and the Good Community

Suggests various ways in which the concept of emotional intelligence (EI) can inform community research and action. Begins by defining EI and reviewing the growing body of research on its contribution to educational, health, and occupational outcomes. Next distinguishes between EI and the related concept of emotional and social competence. Then considers the connection between EI and several topics of interest to community action researchers including prevention and wellness promotion, implementation and dissemination of innovative programs, community development, and the value of diversity. Concludes by suggesting that the ecological perspective can help inform research and practice relating to EI.     

The Meaning vs. The Medical Model in the Empirically Supported Treatment Program: A Consideration of The Empirical Evidence

A review of the debate on the Empirically Supported Treatment Program is presented. It is argued that underlying the specifics of the debate are fundamentally incompatible paradigms: a meaning vs. a medical model. The findings from two gold standard multi-site studies are reviewed to conclude that the control condition meets requirements for an empirically supported treatment. The empirical finding of the failure of clinical training to improve treatment outcomes is explained by the focus on rational factors in training. It is recommended that training of therapists focus on enhancing experiential capacity rather than mastery of manualized treatment approaches.     

Adolescent Psychopathy and the Big Five: Results from Two Samples

The present study examines the relation between psychopathy and the Big Five dimensions of personality in two samples of adolescents. Specifically, the study tests the hypothesis that the aspect of psychopathy representing selfishness, callousness, and interpersonal manipulation (Factor 1) is most strongly associated with low Agreeableness, whereas the aspect of psychopathy representing impulsivity, instability, and social deviance (Factor 2) is associated with low Agreeableness, low Conscientiousness, and high Neuroticism. Data from 13- and 16-year-old boys and their mothers from two samples of the Pittsburgh Youth Study are used to test these hypotheses. Results were consistent across age and rating source in supporting the initial hypotheses, providing support for the construct of juvenile psychopathy and the interpretation of psychopathy as a constellation of traits drawn from a general model of personality functioning.     

A psychometric assessment of a Swedish translation of Spreitzer's empowerment scale

The psychometric properties of a Swedish translation of Spreitzer's (1995a) empowerment scale were assessed. Three parallel assessments were made of data from 1,107 female registered nurses, 758 female assistant nurses, and 107 male registered and assistant nurses. The analyses indicated that the psychometric properties of the scale can be considered satisfactory. Suggestions are made regarding future research in the fields of psychometrics and work- and health-psychology.     

Predicting traumatic stress using emotional intelligence

The study investigated whether emotional intelligence (EI) can predict how individuals respond to traumatic experiences. A random sample of 414 participants (181 male, 233 female) were administered a measure of EI along with the Impact of Event Scale--revised [IES-R; Weiss, D. S. & Marmar, C. R. (1997). The Impact of Events Scale--revised. In J.P. Wilson & T.M. Keane (Eds.), Assessing psychological trauma and PTSD (pp. 399-411). New York: Guilford Press], and the monitoring and blunting questionnaire [MBQ, Anxiety Stress Coping 7 (1994) 53]. The results showed that participants with higher NEIS scores report fewer psychological symptoms relating to their traumatic experiences, that monitors are more likely to have higher NEIS scores than blunters. Traumatic events had a greater impact on females than males, and males had higher EI than females. The implications of these findings for using EI as a predictor for individuals who may experience traumatic stress are discussed.