Groups of Agents with a Leader

We describe simulations of groups of agents that have to reach a target in a two dimensional environment, the performance criterion being the time taken by the last agent to reach the target. If the target is within a given distance from the agent, the agent moves towards the target; otherwise it moves randomly. The simulations contrast groups with and without a leader, where a leader is a member of the group which other members of the group follow as it moves through the environment. We investigate three factors that affect group performance: (1) group size; (2) the presence or absence of an individual agent with the ability to detect targets at a greater distance than those \'visible\' to its companions; (3) the existence of a communication network among group members. The results show that, in groups without communication, leaders have a beneficial effect on group performance, especially in large groups and if the individual with better than average sensory capabilities is the leader of the group. However, in situations where group members can communicate, these results are reversed, with leaders being detrimental, rather than beneficial, to group performanceAgent Based Models, Leaders, Social Simulation, Social Structure, Communication Topologies

Who is the learder? Dynamic role allocation through communication in a population of homogeneous robots

The field of collective robotics has been raising increasing interest in the last few years. In the vast majority of works devoted to collective robotics robots play all the same function, while less attention has been paid to groups of robots with different roles (teams). In this paper we evolve a population of homogeneous robots for dynamically allocating roles through bodily and communicative interactions. Evolved solutions are not only able to efficiently decide who is the leader, but are also robust to changes in team\u27s size, demonstrating the ability of Evolutionary Robotics to find efficient and robust solution to difficult design challenges by relying on selforganizing principles. Our evolved system might be used for improving robots\u27 performance in all the cases in which robots have to accomplish collective tasks for which the presence of a leader might be useful

Robotics Attack!

No abstract availabl

Un sistema robotico occhio-braccio per lo studio dei processi neurali sottostanti a compiti di reaching costruito presso il LARAL

No abstract availableLo scopo di questo scritto ? illustrare l\u27esperienza di costruzione di un sistema occhio-braccio robotico avvenuta presso il "LARAL - Laboratory of Autonomous Robotics and Artificial Life", un laboratorio di ricerca appartenente all\u27Istituto di Scienze e Tecnologie della Cognizione, Consiglio Nazionale delle Ricerche, situato a Roma. Lo scritto illustra non solo l\u27architettura del sistema ma anche la "filosofia" di costruzione di sistemi robotici che ? stata messa a punto durante la sua costruzione. Questa filosofia, partendo dai presupposti per cui l\u27interesse principale del gruppo ? nello studio dei sistemi neurali artificiali e naturali e nello studio del comportamento, ed i robot sono un mezzo per raggiungere questi scopi, ? basata su principi che tendono a minimizzare i costi, i tempi, le conoscenze tecniche e le attrezzature necessarie per lo sviluppo dei robot. Il sistema robotico qui presentato ? stato mostrato in una demo in occasione del workshop di Siena WIVA3 (3? Worskhop Italiano di Vita Artificiale)

Behavioral Restriction Determines Left Attentional Bias: Preliminary Evidences From COVID-19 Lockdown

During the COVID-19 lockdown, individuals were forced to remain at home, hence severely limiting the interaction within environmental stimuli, reducing the cognitive load placed on spatial competences. The effects of the behavioral restriction on cognition have been little examined. The present study is aimed at analyzing the effects of lockdown on executive function prominently involved in adapting behavior to new environmental demands. We analyze non-verbal fluency abilities, as indirectly providing a measure of cognitive flexibility to react to spatial changes. Sixteen students (mean age 20.75; SD 1.34), evaluated before the start of the lockdown (T1) in a battery of psychological tasks exploring different cognitive domains, have been reassessed during lockdown (T2). The assessment included the modified Five-Point Test (m-FPT) to analyze non-verbal fluency abilities. At T2, the students were also administered the Toronto Alexithymia Scale (TAS-20). The restriction of behaviors following a lockdown determines increased non-verbal fluency, evidenced by the significant increase of the number of new drawings. We found worsened verbal span, while phonemic verbal fluency remained unchanged. Interestingly, we observed a significant tendency to use the left part of each box in the m-FPT correlated with TAS-20 and with the subscales that assess difficulty in describing and identifying feelings. Although our data were collected from a small sample, they evidence that the restriction of behaviors determines a leftward bias, suggesting a greater activation of the right hemisphere, intrinsically connected with the processing of non-verbal information and with the need to manage an emotional situation

Basic emotions and adaptation. A computational and evolutionary model

The core principles of the evolutionary theories of emotions declare that affective states represent crucial drives for action selection in the environment and regulated the behavior and adaptation of natural agents in ancestrally recurrent situations. While many different studies used autonomous artificial agents to simulate emotional responses and the way these patterns can affect decision-making, few are the approaches that tried to analyze the evolutionary emergence of affective behaviors directly from the specific adaptive problems posed by the ancestral environment. A model of the evolution of affective behaviors is presented using simulated artificial agents equipped with neural networks and physically inspired on the architecture of the iCub humanoid robot. We use genetic algorithms to train populations of virtual robots across generations, and investigate the spontaneous emergence of basic emotional behaviors in different experimental conditions. In particular, we focus on studying the emotion of fear, therefore the environment explored by the artificial agents can contain stimuli that are safe or dangerous to pick. The simulated task is based on classical conditioning and the agents are asked to learn a strategy to recognize whether the environment is safe or represents a threat to their lives and select the correct action to perform in absence of any visual cues. The simulated agents have special input units in their neural structure whose activation keep track of their actual "sensations" based on the outcome of past behavior. We train five different neural network architectures and then test the best ranked individuals comparing their performances and analyzing the unit activations in each individual's life cycle. We show that the agents, regardless of the presence of recurrent connections, spontaneously evolved the ability to cope with potentially dangerous environment by collecting information about the environment and then switching their behavior to a genetically selected pattern in order to maximize the possible reward. We also prove the determinant presence of an internal time perception unit for the robots to achieve the highest performance and survivability across all conditions

A computational model of the evolution of antipredator behavior in situations with temporal variation of danger using simulated robots

The threat-sensitive predator avoidance hypothesis states that preys are able to assess the level of danger of the environment by using direct and in-direct predator cues. The existence of a neural system which determines this ability has been studied in many animal species like minnows, mosquitoes and wood frogs. What is still under debate is the role of evolution and learning for the emergence of this assessment system. We propose a bio-inspired computing model of how risk management can arise as a result of both factors and prove its impact on fitness in simulated robotic agents equipped with recurrent neural networks and evolved with genetic algorithm. The agents are trained and tested in environments with different level of danger and their performances are ana-lyzed and compared

Boosting effect of regular sport practice in young adults: Preliminary results on cognitive and emotional abilities

Several studies have shown that physical exercise (PE) improves behavior and cognitive functioning, reducing the risk of various neurological diseases, protecting the brain from the detrimental effects of aging, facilitating body recovery after injuries, and enhancing self-efficacy and self-esteem. Emotion processing and regulation abilities are also widely acknowledged to be key to success in sports. In this study, we aim to prove that regular participation in sports enhances cognitive and emotional functioning in healthy individuals. A sample of 60 students (mean age = 22.12; SD = 2.40; M = 30), divided into sportive and sedentary, were subjected to a neuropsychological tests battery to assess their overall cognitive abilities (Raven's Advanced Progressive Matrices, APM), verbal and graphic fluency (Word Fluency Task and modified Five Point Test, m-FPT), as well as their emotional awareness skills (Toronto Alexithymia Scale, TAS-20). Our results showed that sportive students performed better than sedentary ones in all cognitive tasks. Regarding emotional processing abilities, significant differences were found in the TAS-20 total score as well as in the Difficulty Describing Feelings (DDF) subscale and the Difficulty Identifying Feeling (DIF) subscale. Lastly, gender differences were found in the External-Oriented Thinking (EOT) subscale. Overall, our findings evidence that PE has positive effects on cognitive functioning and emotion regulation, suggesting how sports practice can promote mental health and wellbeing