1,720,960 research outputs found
An ontology to improve the first aid service quality
No full textAn ontology is a formal description of knowledge as a set of concepts within a domain and the relationships that hold between them. During the past few years, ontologies became ever more popular. They can be used to describe a lot of scenarios, they are also very useful in the description of real-life situations. Our work stems from a collaboration between two departments of our University, DISIM and MESVA, within a project called eHealth, that, in the first part, focuses on the creation and the querying of an ontology based on anonymous data retrieved from first aid phone services. Once obtained the first aid data and manually created the ontology classes and properties, we are able to automatically insert the data that describes the emergency call received from the first aid operator through a Java application written by us. We analyzed those data through queries, obtaining useful results that can potentially save lives, for example, aiding the operator in the choice of the rescue vehicle to send out for an emergency, depending on the situation
Care Robots Learning Rules of Ethical Behavior Under the Supervision of an Ethical Teacher
Full text linkCare robots are viewed as promising technological development that has the potential to mitigate the increasing imbalance between the number of older adults needing care and a decreasing number of caregivers. However, there are growing concerns about the ethical behavior of these robots. In this work, we show how care robots can learn logical ethical rules of behavior from experience under the supervision of human teacher
Ethical Monitoring and Evaluation of Dialogues with a MAS
Full text linkChatbots are tools aimed at simplifying the interaction between humans and computers, typically used in dialogue systems for various practical purposes. These systems should be built on ethical foundations because their behavior may heavily influence a user (think especially about children). The primary objective of this paper is to present the architecture and prototype implementation of a Multi Agent System (MAS) designed for ethical monitoring and evaluation of a dialogue system. A prototype application, for monitoring and evaluation of chatting agents' (human/artificial) ethical behavior in an online customer service chat point w.r.t their institution/company's codes of ethics and conduct, is developed and presented. We focus on the implementation specifics of the proposed system and the presented prototype application. Future work and open issues with this research are discussed
Logic-based machine learning for transparent ethical agents
Full text linkAutonomous intelligent agents are increasingly engaging in human communities. Thus, they must be expected to follow social and ethical norms of the community in which they are deployed in. In this work we present an approach for developing such ethical agents which are able to develop ethical decision making and judgment capabilities by learning from interactions with the users. Our approach is a logic-based approach and the resulting ethical agents are transparent by design.Autonomous intelligent agents are increasingly engaging in human communities. Thus, they must be expected to follow social and ethical norms of the community in which they are deployed in. In this work we present an approach for developing such ethical agents which are able to develop ethical decision making and judgment capabilities by learning from interactions with the users. Our approach is a logic-based approach and the resulting ethical agents are transparent by design.Autonomous intelligent agents are increasingly engaging in human communities. Thus, they must be expected to follow social and ethical norms of the community in which they are deployed in. In this work we present an approach for developing such ethical agents which are able to develop ethical decision making and judgment capabilities by learning from interactions with the users. Our approach is a logic-based approach and the resulting ethical agents are transparent by design
Ethical Monitoring and Evaluation of Dialogues with a MAS
No full textChatbots are tools aimed at simplifying the interaction between humans and computers, typically used in dialogue systems for various practical purposes. These systems should be built on ethical foundations because their behavior may heavily influence a user (think especially about children). The primary objective of this paper is to present the architecture and prototype implementation of a Multi Agent System (MAS) designed for ethical monitoring and evaluation of a dialogue system. A prototype application, for monitoring and evaluation of chatting agents' (human/artificial) ethical behavior in an online customer service chat point w.r.t their institution/company's codes of ethics and conduct, is developed and presented. We focus on the implementation specifics of the proposed system and the presented prototype application. Future work and open issues with this research are discussed
Extension of constraint-procedural logic-generated environments for deep Q-learning agent training and benchmarking
No full textAutonomous robots can be employed in exploring unknown environments and performing many tasks, such as, e.g. detecting areas of interest, collecting target objects, etc. Deep reinforcement learning (RL) is often used to train this kind of robot. However, concerning the artificial environments aimed at testing the robot, there is a lack of available data sets and a long time is needed to create them from scratch. A good data set is in fact usually produced with high effort in terms of cost and human work to satisfy the constraints imposed by the expected results. In the first part of this paper, we focus on the specification of the properties of the solutions needed to build a data set, making the case of environment exploration. In the proposed approach, rather than using imperative programming, we explore the possibility of generating data sets using constraint programming in Prolog. In this phase, geometric predicates describe a virtual environment according to inter-space requirements. The second part of the paper is focused on testing the generated data set in an AI gym via space search techniques. We developed a Neuro-Symbolic agent built from the following: (i) A deep Q-learning component implemented in Python, able to address via RL a search problem in the virtual space; the agent has the goal to explore a generated virtual environment to seek for a target, improving its performance through a RL process. (ii) A symbolic component able to re-address the search when the Q-learning component gets stuck in a part of the virtual environment; these components stimulate the agent to move to and explore other parts of the environment. Wide experimentation has been performed, with promising results, and is reported, to demonstrate the effectiveness of the approach
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
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