The architecture challenge: Future artificial-intelligence systems will require sophisticated architectures, and knowledge of the brain might guide their construction.

In this commentary, we highlight a crucial challenge posed by the proposal of Lake et al. to introduce key elements of human cognition into deep neural networks and future artificial-intelligence systems: the need to design effective sophisticated architectures. We propose that looking at the brain is an important means of facing this great challenge.

Problematic social media use is statistically predicted by using social media for coping motives and by positive reinforcement processes in individuals with high COVID-19-related stress levels.

It is important to understand the relationship between stress and problematic use of social media (PUSM). However, no study to our knowledge has yet investigated the longitudinal relationship between perceived stress and PUSM via positive and negative reinforcement processes. The present study investigated relationships between COVID-19-pandemic-related stress and PUSM and possible moderating effects of motives for using social media (positive and/or negative reinforcement) during and following a COVID-19-pandemic-related lockdown. Six-hundred-and-sixty participants initially completed a survey including self-report measures of PUSM, COVID-19-pandemic-related stress, and motives for using social media (i.e., for negative reinforcement involving coping and conformity or positive reinforcements involving enhancement and social motives). During the COVID-19 outbreak recovery period, 117 participants again completed the survey. Bayesian analyses revealed that PUSM was associated with higher COVID-19-pandemic-related stress levels and use of social media for coping, conformity, and enhancement purposes. Longitudinally, PUSM symptom worsening was associated with increased use of social media for coping motives regardless of levels of perceived stress. Use of social media for conformity and enhancement purposes moderated relationships between stress levels during lockdown and PUSM symptoms worsening after lockdown. Our findings corroborate the hypothesis that negative reinforcement processes may be key factors in PUSM symptom worsening regardless of perceived stress. Concurrently, high levels of stress may worsen PUSM through positive reinforcement processes.

Using Social Media for Social Motives Moderates the Relationship between Post-Traumatic Symptoms during a COVID-19-Related Lockdown and Improvement of Distress after Lockdown.

Previous research reported inconsistent results on the relationship between social media (SM) use and psychological well-being, suggesting the importance of assessing possible moderators, e.g., motives for SM use. However, no longitudinal study has yet investigated whether, among people who use SM, specific motives for using SM may represent protective/risk factors for the development of psychological distress, especially after a stressful event. Our longitudinal study aimed at assessing the moderating role of motives for using SM (i.e., coping, conformity, enhancement, social motives) in the relationship between COVID-19 pandemic-related post-traumatic stress symptoms during the lockdown and changes in general distress after lockdown. At Time 1 (during the first lockdown in Italy), 660 participants responded to an online survey, reporting their post-traumatic symptoms, motives for using SM, and general distress (i.e., anxiety, depression, and stress symptoms). At Time 2 (three months later, following lockdown), 117 participants volunteered to continue with the follow-up survey assessing general distress symptoms again. Results showed that among those who had experienced more severe post-traumatic symptoms at Time 1, using SM for social motives was associated with more improvement of general distress symptoms. No evidence was found of moderating effects of other motives for SM use. The findings suggest that social connections may have helped to cope with stress during forced confinement, and that SM use may be beneficial for mental health when motivated by maintaining social interactions.

An Embodied Agent Learning Affordances With Intrinsic Motivations and Solving Extrinsic Tasks With Attention and One-Step Planning.

We propose an architecture for the open-ended learning and control of embodied agents. The architecture learns action affordances and forward models based on intrinsic motivations and can later use the acquired knowledge to solve extrinsic tasks by decomposing them into sub-tasks, each solved with one-step planning. An affordance is here operationalized as the agent's estimate of the probability of success of an action performed on a given object. The focus of the work is on the overall architecture while single sensorimotor components are simplified. A key element of the architecture is the use of "active vision" that plays two functions, namely to focus on single objects and to factorize visual information into the object appearance and object position. These processes serve both the acquisition and use of object-related affordances, and the decomposition of extrinsic goals (tasks) into multiple sub-goals (sub-tasks). The architecture gives novel contributions on three problems: (a) the learning of affordances based on intrinsic motivations; (b) the use of active vision to decompose complex extrinsic tasks; (c) the possible role of affordances within planning systems endowed with models of the world. The architecture is tested in a simulated stylized 2D scenario in which objects need to be moved or "manipulated" in order to accomplish new desired overall configurations of the objects (extrinsic goals). The results show the utility of using intrinsic motivations to support affordance learning; the utility of active vision to solve composite tasks; and the possible utility of affordances for solving utility-based planning problems.

Sensorimotor Contingencies as a Key Drive of Development: From Babies to Robots.

Much current work in robotics focuses on the development of robots capable of autonomous unsupervised learning. An essential prerequisite for such learning to be possible is that the agent should be sensitive to the link between its actions and the consequences of its actions, called sensorimotor contingencies. This sensitivity, and more particularly its role as a key drive of development, has been widely studied by developmental psychologists. However, the results of these studies may not necessarily be accessible or intelligible to roboticians. In this paper, we review the main experimental data demonstrating the role of sensitivity to sensorimotor contingencies in infants' acquisition of four fundamental motor and cognitive abilities: body knowledge, memory, generalization, and goal-directedness. We relate this data from developmental psychology to work in robotics, highlighting the links between these two domains of research. In the last part of the article we present a blueprint architecture demonstrating how exploitation of sensitivity to sensorimotor contingencies, combined with the notion of "goal," allows an agent to develop new sensorimotor skills. This architecture can be used to guide the design of specific computational models, and also to possibly envisage new empirical experiments.