A SYSTEM FOR LOGIC-BASED INTELLIGENT VIRTUAL AGENTS

2004 ◽  
Vol 13 (03) ◽  
pp. 593-621 ◽  
Author(s):  
G. ANASTASSAKIS ◽  
T. PANAYIOTOPOULOS
Keyword(s):  
Artificial Intelligence ◽  
Virtual Environments ◽  
Intelligent Agent ◽  
Virtual Agents ◽  
Agent System ◽  
Intelligent Virtual Agents ◽  
Potential Benefits ◽  
Evaluation Stage ◽  
Educational Applications ◽  
Definition Of

Combination of logic-based artificial intelligence with virtual reality in intelligent agent systems is an approach not extensively sought after to date. It is our belief that significant gain is to be expected if the technical challenges involved are overcome. In this paper, we describe the mVlTAL intelligent agent system, which is our latest effort towards this direction. The system is a contemporary intelligent agent system with applications in numerous areas, including intelligent virtual environments and formal artificial intelligence research. The system focuses largely on logic-based approaches, which are present in almost every aspect of it, including modeling, knowledge representation, definition of agent behaviors and inter-agent communication. In addition, virtual manifestation of the world and agents is also an inherent characteristic of the system. The system, even if still in a development and evaluation stage, has already been employed in experimental and educational applications, demonstrating the potential benefits of such an approach.

A New Framework for Intelligent Semantic Web Services Based on GAIVAs

2010 ◽  
pp. 38-62
Author(s):  
Iglesias Andrés
Keyword(s):  
Artificial Intelligence ◽  
User Interface ◽  
Web Services ◽  
Semantic Web ◽  
Semantic Web Services ◽  
Virtual Agents ◽  
Web Pages ◽  
Artificial Intelligence Techniques ◽  
Intelligent Virtual Agents ◽  
New Framework

The Semantic Web has been recently developed to provide end users with suitable tools and strategies to process information from their Web pages. The Intelligent Semantic Web Services is a new approach aimed at extending Semantic Web capabilities for Services by applying Artificial Intelligence techniques while maintaining the good properties of the standard Semantic Web schemes. However, many current Web services neither consider this approach nor include a powerful user-interface and, consequently, are very limited and difficult to use. This paper introduces a new framework for Intelligent Semantic Web Services that overcomes these drawbacks. Our approach is based on the Graphical Autonomous Intelligent Virtual Agents (GAIVAs), virtual agents that exhibit a human-like appearance and behaviour and are able to take intelligent decisions and perform actions without human intervention. To this purpose, the framework comprises a collection of powerful Artificial Intelligence techniques along with a natural and intuitive Graphical User Interface.

Virtual Reality in Object Location

2021 ◽  
pp. 307-324
Author(s):  
Graciela Lara López
Keyword(s):  
Virtual Reality ◽  
Natural Language ◽  
Computational Model ◽  
Everyday Life ◽  
Virtual Environments ◽  
Computer Technology ◽  
Object Location ◽  
Virtual Agents ◽  
Intelligent Virtual Agents

Currently, virtual reality (VR) is a computer technology that is growing in terms of developments and discoveries. Virtual reality has been introduced in different areas due to the growing interest it has caused in people. The development of applications with virtual reality is increasingly varied, covering activities, tasks, or processes of everyday life in the fields of industry, education, medicine, tourism, art, entertainment, design, and modeling of objects, among others. This chapter will focus on describing the latest advances and developments in virtual reality within the scope of representing reality in the process of locating objects. With the support of virtual environments and intelligent virtual agents, the author has managed to develop a computational model that generates indications in natural language, for the location of objects considering spatial and cognitive aspects of the users.

Biofeedback and Virtual Environments

2011 ◽  
Vol 9 (4) ◽  
pp. 377-395 ◽  
Author(s):  
Erik Champion ◽  
Andrew Dekker
Keyword(s):  
Artificial Intelligence ◽  
Virtual Environments ◽  
Virtual Environment ◽  
Digital Environment ◽  
Cognitive Loading ◽  
Potential Benefits ◽  
Dynamic Modification

This paper explains potential benefits of indirect biofeedback used within interactive virtual environments, and reflects on an earlier study that allowed for the dynamic modification of a virtual environment's graphic shaders, music and artificial intelligence, based on the biofeedback of the player. The aim was to determine which augmented effects aided or discouraged engagement in the game. Conversely, biofeedback can help calm down rather than stress participants, and attune them to different ways of interacting within a virtual environment. Other advantages of indirect biofeedback might include increased personalization, thematic object creation, atmospheric augmentation, filtering of information, and tracking of participants' understanding and engagement. Such features may help designers create more intuitive virtual environments with more thematically appropriate interaction while reducing cognitive loading on the participants. Another benefit would be more engaged clients with a better understanding of the richness and complexity of a digital environment.

Being on Guard: Intelligent Virtual Agents Reporting Information from Collaborative Virtual Environments

2005 ◽  
Vol 14 (4) ◽  
pp. 423-433
Author(s):  
Pilar Herrero ◽  
Chris Greenhalgh ◽  
Angélica de Antonio
Keyword(s):  
Virtual Environments ◽  
Spatial Model ◽  
Human Perception ◽  
Computer Supported Cooperative Work ◽  
Virtual Agents ◽  
Collaborative Virtual Environments ◽  
Perceptual Model ◽  
Key Concepts ◽  
Intelligent Virtual Agents ◽  
Auditory Acuity

An important property of intelligent virtual agents (IVAs) and multiintelligent virtual agents systems (mIVAS) is their capability to acquire/perceive information from their environment. In this paper we present an auditory perceptual model for IVAs and mIVAS, which extends and reinterprets the key concepts of one of the awareness models developed for computer supported cooperative work (CSCW) applications, the spatial model of interaction (SMI). This perceptual model also introduces some factors typical of human perception—such as auditory acuity—as well as others associated with the sound source and its propagation with the aim of making perception in this kind of system more humanlike.

Applying Artificial Intelligence in CRM: Case Studies of Intelligent Virtual Agents and Pegasystems

2012 ◽  
Vol 182-183 ◽  
pp. 878-882
Author(s):  
Te Fu Chen
Keyword(s):  
Artificial Intelligence ◽  
Case Studies ◽  
Customer Service ◽  
Virtual Agents ◽  
Customer Support ◽  
Differences Of Opinion ◽  
Intelligent Virtual Agents ◽  
Applications Of Ai

It is highly technical and specialized for AI research, and deeply divided into subfields that often fail to communicate with each other. Subfields have grown up around particular institutions, the work of individual researchers, the solution of specific problems, longstanding differences of opinion about how AI should be done and the application of widely differing tools. The central problems of AI include such traits as reasoning, knowledge, planning, learning, communication, perception and the ability to move and manipulate objects. Currently, in the form of applications of AI, is slowly making its way out of laboratories into the mainstream market. The study reviews AI and CRM, the evolution of CRM: XRM, the applications of AI in CRM including customer support automation, automated online assistant and online and telephone customer service. Finally, the study examines the applications of AI in CRM via two case studies of Intelligent Virtual Agents (IVAs) and Pegasystems to link the theories and practices.

scholarly journals A short guide for medical professionals in the era of artificial intelligence

2020 ◽  
Vol 3 (1) ◽  
Author(s):  
Bertalan Meskó ◽  
Marton Görög
Keyword(s):  
Artificial Intelligence ◽  
Medical Professional ◽  
Clinical Validation ◽  
Delivery Of Healthcare ◽  
Practice Of Medicine ◽  
Potential Benefits ◽  
Definition Of ◽  
Near Future ◽  
News Headlines ◽  
Simple Definition

Abstract Artificial intelligence (A.I.) is expected to significantly influence the practice of medicine and the delivery of healthcare in the near future. While there are only a handful of practical examples for its medical use with enough evidence, hype and attention around the topic are significant. There are so many papers, conference talks, misleading news headlines and study interpretations that a short and visual guide any medical professional can refer back to in their professional life might be useful. For this, it is critical that physicians understand the basics of the technology so they can see beyond the hype, evaluate A.I.-based studies and clinical validation; as well as acknowledge the limitations and opportunities of A.I. This paper aims to serve as a short, visual and digestible repository of information and details every physician might need to know in the age of A.I. We describe the simple definition of A.I., its levels, its methods, the differences between the methods with medical examples, the potential benefits, dangers, challenges of A.I., as well as attempt to provide a futuristic vision about using it in an everyday medical practice.

Design of Believable Intelligent Virtual Agents

2005 ◽  
pp. 177-211 ◽  
Author(s):  
Pilar Herrero ◽  
Ricardo Imbert
Keyword(s):  
Virtual Environments ◽  
Spatial Model ◽  
Cooperative Work ◽  
Computer Supported Cooperative Work ◽  
The Other ◽  
High Price ◽  
Virtual Agents ◽  
Intelligent Virtual Agents ◽  
High Level ◽  
Graphical Design

Virtual environments (VEs) have a set of characteristics that make them hard to be designed and implemented: distributed nature, high-level graphical design, technology novelty, and so forth. Because of the criticism or the repetitiveness of some roles played in them, some of the characters of the VEs usually must be automated. The risk is to pay a too high price, losing attractiveness, usability, or believability. The solution proposed in this chapter is to control the automated avatars by associating them with software agents, becoming intelligent virtual agents (IVAs). With this aim, an architecture to manage the perception and cognition of the agent is described. On one hand, the perceptual module of this architecture consists of a human-like model, based on one of the most successful awareness models in computer-supported cooperative work (CSCW), called the Spatial Model of Interaction (SMI). On the other hand, the cognitive module proposes an easy-to-configure structure, providing it with the precise mechanisms to exhibit reactive, deliberative or, even, more sophisticated social behaviors, incrementing the believability of the IVA in the VE.

scholarly journals Evaluation of Intelligent Agent Frameworks for Human Learning

2011 ◽  
Vol 1 (3) ◽  
pp. 45 ◽  
Author(s):  
Mohamed Soliman ◽  
Christian Guetl
Keyword(s):  
Intelligent Agents ◽  
Intelligent Agent ◽  
Pedagogical Agents ◽  
Virtual Agents ◽  
Educational Value ◽  
Learning Platform ◽  
New Learning ◽  
Intelligent Virtual Agents ◽  
Learning Scenarios ◽  
Multi Agent

<p align="left">&nbsp;</p><p><strong><span style="font-size: xx-small;">Pedagogical Agents are intelligent agents supporting learning in virtual learning environments, VLE. The use of the multi-agent society model inhabited with intelligent virtual agents has shown to provide several benefits to learning. This paper reviews intelligent agents for learning and shows their educational value while demonstrating the new learning possibilities supported by them. Towards the objective of efficiently utilizing the agents in a distributed learning platform, the paper provides an evaluation of intelligent agent development frameworks. This evaluation will provide valuable information to those employing and integrating intelligent agents for different types of VLE with a view towards creating new learning scenarios </span></strong></p>

Attitudes of Medical Workers Toward Artificial Intelligence in Ophthalmology: A Comparative Survey (Preprint)

2020 ◽  
Author(s):  
Weihua Yang ◽  
Bo Zheng ◽  
Maonian Wu ◽  
Shaojun Zhu ◽  
Hongxia Zhou ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Medical Ethics ◽  
Online Survey ◽  
Medical Professionals ◽  
Medical Field ◽  
Acceptance Level ◽  
Professional Workers ◽  
Basic Understanding ◽  
Comparative Survey ◽  
Definition Of

BACKGROUND Artificial intelligence (AI) is widely applied in the medical field, especially in ophthalmology. In the development of ophthalmic artificial intelligence, some problems worthy of attention have gradually emerged, among which the ophthalmic AI-related recognition issues are particularly prominent. That is to say, currently, there is a lack of research into people's familiarity with and their attitudes toward ophthalmic AI. OBJECTIVE This survey aims to assess medical workers’ and other professional technicians’ familiarity with AI, as well as their attitudes toward and concerns of ophthalmic AI. METHODS An electronic questionnaire was designed through the Questionnaire Star APP, an online survey software and questionnaire tool, and was sent to relevant professional workers through Wechat, China’s version of Facebook or WhatsApp. The participation was based on a voluntary and anonymous principle. The questionnaire mainly consisted of four parts, namely the participant’s background, the participant's basic understanding of AI, the participant's attitude toward AI, and the participant's concerns about AI. A total of 562 participants were counted, with 562 valid questionnaires returned. The results of the questionnaires are displayed in an Excel 2003 form. RESULTS A total of 562 professional workers completed the questionnaire, of whom 291 were medical workers and 271 were other professional technicians. About 37.9% of the participants understood AI, and 31.67% understood ophthalmic AI. The percentages of people who understood ophthalmic AI among medical workers and other professional technicians were about 42.61% and 15.6%, respectively. About 66.01% of the participants thought that ophthalmic AI would partly replace doctors, with about 59.07% still having a relatively high acceptance level of ophthalmic AI. Meanwhile, among those with ophthalmic AI application experiences (30.6%), respectively about 84.25% of medical professionals and 73.33% of other professional technicians held a full acceptance attitude toward ophthalmic AI. The participants expressed concerns that ophthalmic AI might bring about issues such as the unclear definition of medical responsibilities, the difficulty of ensuring service quality, and the medical ethics risks. And among the medical workers and other professional technicians who understood ophthalmic AI, 98.39%, and 95.24%, respectively, said that there was a need to increase the study of medical ethics issues in the ophthalmic AI field. CONCLUSIONS Analysis of the questionnaire results shows that the medical workers have a higher understanding level of ophthalmic AI than other professional technicians, making it necessary to popularize ophthalmic AI education among other professional technicians. Most of the participants did not have any experience in ophthalmic AI, but generally had a relatively high acceptance level of ophthalmic AI, believing that doctors would partly be replaced by it and that there was a need to strengthen research into medical ethics issues of the field.

Europe

2020 ◽  
pp. 649-666
Author(s):  
Andrea Renda
Keyword(s):  
Artificial Intelligence ◽  
Digital Technology ◽  
Policy Framework ◽  
Expert Group ◽  
Ethical Guidelines ◽  
Ethical Implications ◽  
Strong Focus ◽  
Ethics Guidelines ◽  
Definition Of ◽  
High Level

This chapter assesses Europe’s efforts in developing a full-fledged strategy on the human and ethical implications of artificial intelligence (AI). The strong focus on ethics in the European Union’s AI strategy should be seen in the context of an overall strategy that aims at protecting citizens and civil society from abuses of digital technology but also as part of a competitiveness-oriented strategy aimed at raising the standards for access to Europe’s wealthy Single Market. In this context, one of the most peculiar steps in the European Union’s strategy was the creation of an independent High-Level Expert Group on AI (AI HLEG), accompanied by the launch of an AI Alliance, which quickly attracted several hundred participants. The AI HLEG, a multistakeholder group including fifty-two experts, was tasked with the definition of Ethics Guidelines as well as with the formulation of “Policy and Investment Recommendations.” With the advice of the AI HLEG, the European Commission put forward ethical guidelines for Trustworthy AI—which are now paving the way for a comprehensive, risk-based policy framework.

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