Developing Self-Awareness in Robots via Inner Speech

The experience of inner speech is a common one. Such a dialogue accompanies the introspection of mental life and fulfills essential roles in human behavior, such as self-restructuring, self-regulation, and re-focusing on attentional resources. Although the underpinning of inner speech is mostly investigated in psychological and philosophical fields, the research in robotics generally does not address such a form of self-aware behavior. Existing models of inner speech inspire computational tools to provide a robot with this form of self-awareness. Here, the widespread psychological models of inner speech are reviewed, and a cognitive architecture for a robot implementing such a capability is outlined in a simplified setup

Robots as intelligent assistants to face COVID-19 pandemic

Motivation: The epidemic at the beginning of this year, due to a new virus in the coronavirus family, is causing many deaths and is bringing the world economy to its knees. Moreover, situations of this kind are historically cyclical. The symptoms and treatment of infected patients are, for better or worse even for new viruses, always the same: More or less severe flu symptoms, isolation and full hygiene. By now man has learned how to manage epidemic situations, but deaths and negative effects continue to occur. What about technology? What effect has the actual technological progress we have achieved? In this review, we wonder about the role of robotics in the fight against COVID. It presents the analysis of scientific articles, industrial initiatives and project calls for applications from March to now highlighting how much robotics was ready to face this situation, what is expected from robots and what remains to do. Results: The analysis was made by focusing on what research groups offer as a means of support for therapies and prevention actions. We then reported some remarks on what we think is the state of maturity of robotics in dealing with situations like COVID-19

A Quantum Planner for Robot Motion

The possibility of integrating quantum computation in a traditional system appears to be a viable route to drastically improve the performance of systems endowed with artificial intelligence. An example of such processing consists of implementing a teleo-reactive system employing quantum computing. In this work, we considered the navigation of a robot in an environment where its decisions are drawn from a quantum algorithm. In particular, the behavior of a robot is formalized through a production system. It is used to describe the world, the actions it can perform, and the conditions of the robot's behavior. According to the production rules, the planning of the robot activities is processed in a recognize-act cycle with a quantum rule processing algorithm. Such a system aims to achieve a significant computational speed-up

A global workspace theory model for trust estimation in human-robot interaction

Successful and genuine social connections between humans are based on trust, even more when the people involved have to collaborate to reach a shared goal. With the advent of new findings and technologies in the field of robotics, it appears that this same key factor that regulates relationships between humans also applies with the same importance to human-robot interactions (HRI). Previous studies have proven the usefulness of a robot able to estimate the trustworthiness of its human collaborators and in this position paper we discuss a method to extend an existing state-of-the-art trust model with considerations based on social cues such as emotions. The proposed model follows the Global Workspace Theory (GWT) principles to build a novel system able to combine multiple specialised expert systems to determine whether the partner can be considered trustworthy or not. Positive results would demonstrate the usefulness of using constructive biases to enhance the teaming skills of social robots

Inside the robot’s mind during human-robot interaction

Humans and robots collaborating and cooperating for pursuing a shared objective need to rely on the other for carrying out an effective decision process and for updating knowledge when necessary in a dynamic environment. Robots have to behave as they were human teammates. To model the cognitive process of robots during the interaction, we developed a cognitive architecture that we implemented employing the BDI (belief, desire, intention) agent paradigm. In this paper, we focus on how to let the robot show to the human its reasoning process and how its knowledge on the work environment grows. We realized a framework whose heart is a simulator that serves the human as a window on the robot’s mind

Measuring Relations Between Concepts In Conceptual Spaces

The highly influential framework of conceptual spaces provides a geometric way of representing knowledge. Instances are represented by points in a high-dimensional space and concepts are represented by regions in this space. Our recent mathematical formalization of this framework is capable of representing correlations between different domains in a geometric way. In this paper, we extend our formalization by providing quantitative mathematical definitions for the notions of concept size, subsethood, implication, similarity, and betweenness. This considerably increases the representational power of our formalization by introducing measurable ways of describing relations between concepts.Comment: Accepted at SGAI 2017 (http://www.bcs-sgai.org/ai2017/). The final publication is available at Springer via https://doi.org/10.1007/978-3-319-71078-5_7. arXiv admin note: substantial text overlap with arXiv:1707.05165, arXiv:1706.0636

Moral Mediators in the Metaverse: Exploring Artificial Morality through a Talking Cricket Paradigm

As technological innovations continue to shape our social interactions, the Metaverse introduces immersive experiences that reflect real-life practices, accessible by users through their avatars. However, these interactions also bring forth potential negative aspects, including discrimination and cyberbullying. While current automatic detection systems exist, educating users on appropriate behaviour remains crucial. Leveraging recent advancements in Artificial Intelligence, the paper focuses on creating virtual AI-controlled moral agents within the Metaverse to guide users in dealing with moral dilemmas. The research aims to understand how such agents impact users' perceptions and behaviours in ethically challenging virtual environments

Response to erlotinib in a patient with lung adenocarcinoma harbouring the EML4-ALK translocation: A case report.

Lung cancer is the leading cause of cancer-associated mortality worldwide, and the mainstay of treatment remains to be personalised therapy. Tyrosine kinase inhibitors of the epidermal growth factor receptor (EGFR-TKIs) have been reported to exert a significant impact in the treatment of non-small cell lung cancer (NSCLC), particularly in patients harbouring mutations in the EGFR gene. The echinoderm microtubule-associated protein-like 4-anaplastic lymphoma kinase (EML4-ALK) gene translocation has been described in a subset of patients with NSCLC and possesses potent oncogenic activity. This translocation represents one of the most novel molecular targets in the treatment of NSCLC. Patients who harbour the EML4-ALK rearrangement possess lung tumours that lack EGFR or K-ras mutations. The present study reports the case of a patient possessing the EML4-ALK rearrangement that was initially treated with erlotinib and achieved a lasting clinical response. To the best of our knowledge, the current study is the first report of a clinical response to EGFR-TKI in a patient with lung adenocarcinoma harbouring the EML4-ALK fusion gene, but no EGFR mutations. However, as the disease progressed, the ALK gene status of the tumour was investigated, and based upon a positive result, the patient was treated with crizotinib and achieved a complete response. In conclusion, the present study suggests that the EML4-ALK rearrangement is not always associated with resistance to EGFR-TKIs. Further studies are required to clarify the biological features of these tumours and to investigate the mechanisms underlying the primary resistance to EGFR-TKIs when the EML4-ALK rearrangement is present

Let-7g and miR-21 expression in non-small cell lung cancer: correlation with clinicopathological and molecular features

MicroRNAs (miRNAs) play a key role in cancer pathogenesis and are involved in several human cancers, including non-small cell lung cancer (NSCLC). This study evaluated Let-7g and miR-21 expression by quantitative real-time PCR in 80 NSCLC patients and correlated the results with their main clinicopathological and molecular features. MiR-21 expression was significantly higher in NSCLC tissues compared to non-cancer lung tissues (p<0.0001), while no significant changes in Let-7g expression were observed between the tumor and normal lung tissues. Target prediction analysis led to the identification of 26 miR-21 and 24 Let-7g putative target genes that play important roles in cancer pathogenesis and progression. No significant association was observed between the analysed miRNAs and the main clinicopathological or molecular characteristics of the NSCLC patients, although both miRNAs were downregulated in squamous cell carcinomas compared to adenocarcinomas. Noteworthy, we observed a significant association between low Let-7g expression and metastatic lymph nodes at diagnosis (p=0.046), as well as between high miR-21 expression and K-Ras mutations (p=0.0003). Survival analysis did not show any significant correlation between prognosis and the analysed miRNAs, although the patients with a high Let-7g and miR-21 expression showed a significantly lower short-term progression-free survival (p=0.01 and p=0.0003, respectively) and overall survival (p=0.023 and p=0.0045, respectively). In conclusion, we showed that Let-7g and miR-21 expression was deregulated in NSCLC and we demonstrated a strong relationship between miR-21 overexpression and K-Ras mutations. Our data indicate that Let-7g and miR-21 profiling combined with the determination of K-Ras mutational status may be considered a useful biomarker for a more effective molecular characterization and clinical management of NSCLC patients