Smart Agent and it’s effect on Artificial Intelligence : A Review Study

Current networking technologies, as well as the ready availability of large quantities of data and knowledge on the Internet-based Infosphere, offer tremendous opportunities for providing more abundant and reliable information to decision makers and decision support systems. The use of the Internet has increased at a breakneck pace. Some prevailing features of the Infosphere, however, have hindered successful use of the Internet by humans or decision support machine systems. To begin with, the information available on the internet is disorganized, multi-modal, and spread around the globe on server pages. Second, every day, the number and variety of data sources and services grows dramatically. In addition, the availability, type, and dependability of information services are all changing all the time. Third, the same piece of knowledge can be obtained from a number of different sources. Fourth, due to the complex existence of information sources and possible information updating and maintenance issues, information is vague and probably incorrect. As a result, collecting, filtering, evaluating, and using information in problem solving is becoming increasingly difficult for a human or computer device. As a consequence, identifying information sources, accessing, filtering, and incorporating data in support of decision-making, as well as managing information retrieval and problem-solving efforts of information sources and decision-making processes, has become a critical challenge. To fix this issue, the idea of "Intelligent Software Agents" has been suggested. Although a precise definition of an intelligent agent is still a work in progress, the current working definition is that Intelligent Software Agents are programs that act on behalf of their human users to perform laborious information gathering tasks such as locating and accessing information from various on-line information sources, resolving inconsistencies in the retrieved information, filtering out irrelevant data.

Identifying research gaps: A review of virtual patient education and self-management

BACKGROUND: Avatars in Virtual Reality (VR) can not only represent humans, but also embody intelligent software agents that communicate with humans, thus enabling a new paradigm of human-machine interaction. OBJECTIVE: The research agenda proposed in this paper by an interdisciplinary team is motivated by the premise that a conversation with a smart agent avatar in VR means more than giving a face and body to a chatbot. Using the concrete communication task of patient education, this research agenda is rather intended to explore which patterns and practices must be constructed visually, verbally, para- and nonverbally between humans and embodied machines in a counselling context so that humans can integrate counselling by an embodied VR smart agent into their thinking and acting in one way or another. METHODS: The scientific literature in different bibliographical databases was reviewed. A qualitative narrative approach was applied for analysis. RESULTS: A research agenda is proposed which investigates how recurring consultations of patients with healthcare professionals are currently conducted and how they could be conducted with an embodied smart agent in immersive VR. CONCLUSIONS: Interdisciplinary teams consisting of linguists, computer scientists, visual designers and health care professionals are required which need to go beyond a technology-centric solution design approach. Linguists’ insights from discourse analysis drive the explorative experiments to identify test and discover what capabilities and attributes the smart agent in VR must have, in order to communicate effectively with a human being.

Empowering Communications in Vehicular Networks with an Intelligent Blockchain-Based Solution

Blockchains have emerged over time as a reliable and secure way to record transactions in an immutable manner in a wide range of application domains. However, current related solutions are not yet capable of appropriately checking the authenticity of data when their volumes are huge. They are not also capable of updating Blockchain data blocks and synchronizing them within reasonable timeframes. This is the case within the specific context of Blockchain vehicular networks, where these solutions are commonly cumbersome when attempting to add new vehicles to the network. In order to address these problems, we propose in this paper a new Blockchain-based solution that intelligently implement selective communication and collaborative endorsement approaches to reduce communications between vehicles. Our solution represents the vehicles of the Blockchain as intelligent software agents with a Belief–Desire–Intention (BDI) architecture. Furthermore, we propose an approach based on multi-endorsement levels to exchange data of varying sensitive categories. This approach, which is based on endorsing scores, is also used to shorten the admission of new vehicles into the Blockchain. We run simulations using the Hyperledger Fabric Blockchain tool. Results show the efficiency of our solution in reducing the processing times of transactions within two different scenarios.

Next-Generation Programming Learning Platform: Architecture and Challenges

With the rapid development of information technology, programming has become a vital skill. An online judge system can be used as a programming education platform, where the daily activities of users and judges are used to generate useful learning objects (e.g., tasks, solution codes, evaluations). Intelligent software agents can utilize such objects to create an ecosystem. To implement such an ecosystem, a generic architecture that covers the whole lifecycle of data on the platform and the functionalities of an e-learning system should take into account the particularities of the online judge system. In this paper, an architecture that implements such an ecosystem based on an online judge system is proposed. The potential benefits and research challenges are discussed.

An introductory preview of Autonomous Intelligent Cyber-defense Agent reference architecture, release 2.0

The North Atlantic Treaty Organization (NATO) Research Task Group IST-152 developed a concept and a reference architecture for intelligent software agents performing active, largely autonomous cyber-defense actions on military assets. The group released a detailed report, briefly reviewed in this article, where such an agent is referred to as an Autonomous Intelligent Cyber-defense Agent (AICA). In a conflict with a technically sophisticated adversary, NATO military networks will operate in a heavily contested battlefield. Enemy malware will likely infiltrate and attack friendly networks and systems. Today’s reliance on human cyber defenders will be untenable on the future battlefield. Instead, artificially intelligent agents, such as AICAs, will be necessary to defeat the enemy malware in an environment of potentially disrupted communications where human intervention may not be possible. The IST-152 group identified specific capabilities of AICA. For example, AICA will have to be capable of autonomous planning and execution of complex multi-step activities for defeating or degrading sophisticated adversary malware, with the anticipation and minimization of resulting side effects. It will have to be capable of adversarial reasoning to battle against a thinking, adaptive malware. Crucially, AICA will have to keep itself and its actions as undetectable as possible, and will have to use deceptions and camouflage. The report identifies the key functions and components and their interactions for a potential reference architecture of such an agent, as well as a tentative roadmap toward the capabilities of AICA.

AVANCES EN INTERACCIÓN HOMBRE – MÁQUINA

AVANCES EN INTERACCIÓN HOMBRE – MÁQUINA NEW ADVANCES IN MAN – MACHINE INTERACTION Fernando Ramírez - Icaza. Manuel Villavicencio 1331, Lima -14, Perú. DOI: https://doi.org/10.33017/RevECIPeru2010.0005/ RESUMEN En el presente artículo de investigación se pone énfasis en las diferentes formas de Interacción Hombre – Máquina, las cuales se masificarán, en un futuro no muy lejano, a través de Robots Físicos, Robots Virtuales, u órdenes procedentes del cerebro humano procesadas por electrodos capaces de captar la energía propia del proceso bioquímico entre las neuronas y por ende leer el pensamiento humano. Los robots durante la interacción Hombre – Máquina deben constantemente tomar decisiones para lo cual es importante tener en consideración en la construcción de las Bases de Conocimientos los siguientes pasos: análisis de la información, análisis de la representación de la información sobre la base de criterios taxonómicos, identificación de axiomas, sugerencia de mecanismo de protección de axiomas, sugerencia de mecanismo de inferencia, evaluación de Sistemas Formales, recomendación del Sistema Formal más conveniente y expresivo para la representación de cada uno de los axiomas, recomendación al equipo de Ingenieros de Software el mecanismo más idóneo para la incorporación de axiomas y reglas. Finalmente, se expone las conclusiones y reflexiones del autor sobre este nuevo paradigma de las Ciencias Computacionales. Palabras clave: Inteligencia Artificial, Interacción Hombre - Máquina, Robots, Bases de Conocimientos, Agentes Inteligentes de Software o Softbots, Verbots. ABSTRACT This article emphasizes research on different forms of interaction between man - machine, which will widely spread out in a not too distant future through physical robots, virtual robots, or orders issued by the human brain processed by electrodes capable of capturing the energy of the biochemical process between neurons and thus read human thought. Robots during Man – Machine interaction must constantly make decisions. Therefore, when building knowledge bases it is important to consider the following steps: analysis of data, analysis of the representation of information based on taxonomic criteria, identification of axioms, suggested protective mechanism of axioms, inference mechanism suggestion, evaluation of formal systems, recommendation of formal systems, recommendation of the most convenient and expressive formal system for the representation of each of the axioms, recommendation to the team of software engineers of the most appropriate mechanism for incorporating axioms & rules. Finally, it draws conclusions and reflections of the author on this new paradigm of Computer Sciences. Keywords: Artificial Intelligence, Interaction Man - Machine, Robots, Knowledge Bases, Intelligent Software Agents or Softbots, Verbots.