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>

scholarly journals Perceptions on Authenticity in Chat Bots

2018 ◽  
Vol 2 (3) ◽  
pp. 60 ◽  
Author(s):  
Mario Neururer ◽  
Stephan Schlögl ◽  
Luisa Brinkschulte ◽  
Aleksander Groth
Keyword(s):  
Intelligent Agents ◽  
Social Intelligence ◽  
Virtual Agents ◽  
Learning From Experience ◽  
Alan Turing ◽  
Conversational Behavior ◽  
Artificial Intelligence Technology ◽  
Intelligent Virtual Agents ◽  
Open Question ◽  
Question Survey

In 1950, Alan Turing proposed his concept of universal machines, emphasizing their abilities to learn, think, and behave in a human-like manner. Today, the existence of intelligent agents imitating human characteristics is more relevant than ever. They have expanded to numerous aspects of daily life. Yet, while they are often seen as work simplifiers, their interactions usually lack social competence. In particular, they miss what one may call authenticity. In the study presented in this paper, we explore how characteristics of social intelligence may enhance future agent implementations. Interviews and an open question survey with experts from different fields have led to a shared understanding of what it would take to make intelligent virtual agents, in particular messaging agents (i.e., chat bots), more authentic. Results suggest that showcasing a transparent purpose, learning from experience, anthropomorphizing, human-like conversational behavior, and coherence, are guiding characteristics for agent authenticity and should consequently allow for and support a better coexistence of artificial intelligence technology with its respective users.

Intelligent Agents in a Trust Environment

2002 ◽  
pp. 98-108
Author(s):  
Rahul Singh ◽  
Mark A. Gill
Keyword(s):  
Distributed System ◽  
Intelligent Agents ◽  
Single Agent ◽  
Intelligent Agent ◽  
The Internet ◽  
Commercial Activity ◽  
Agent Based ◽  
Trust Relationships ◽  
Multi Agent ◽  
Oriented Activity

Intelligent agents and multi-agent technologies are an emerging technology in computing and communications that hold much promise for a wide variety of applications in Information Technology. Agent-based systems range from the simple, single agent system performing tasks such as email filtering, to a very complex, distributed system of multiple agents each involved in individual and system wide goal-oriented activity. With the tremendous growth in the Internet and Internet-based computing and the explosion of commercial activity on the Internet in recent years, intelligent agent-based systems are being applied in a wide variety of electronic commerce applications. In order to be able to act autonomously in a market environment, agents must be able to establish and maintain trust relationships. Without trust, commerce will not take place. This research extends previous work in intelligent agents to include a mechanism for handling the trust relationship and shows how agents can be fully used as intermediaries in commerce.

REINFORCEMENT LEARNING FOR DECISION-MAKING IN A BUSINESS SIMULATOR

2012 ◽  
Vol 11 (05) ◽  
pp. 935-960 ◽  
Author(s):  
JAVIER GARCÍA ◽  
FERNANDO BORRAJO ◽  
FERNANDO FERNÁNDEZ
Keyword(s):  
Decision Making ◽  
Reinforcement Learning ◽  
Business Education ◽  
Intelligent Agents ◽  
Continuous Variables ◽  
Web Based ◽  
Business Decision ◽  
Decision Variables ◽  
Learning Scenarios ◽  
Multi Agent

Business simulators are powerful tools for both supporting the decision-making process of business managers as well as for business education. An example is SIMBA (SIMulator for Business Administration), a powerful simulator which is currently used as a web-based platform for business education in different institutions. In this paper, we propose the application of reinforcement learning (RL) for the creation of intelligent agents that can manage virtual companies in SIMBA. This application is not trivial, given the particular intrinsic characteristics of SIMBA: it is a generalized domain where hundreds of parameters modify the domain behavior; it is a multi-agent domain where both cooperation and competition among different agents can coexist; it is required to set dozens of continuous decision variables for a given business decision, which is made only after the study of hundreds of continuous variables. We will demonstrate empirically that all these challenges can be overcome through the use of RL, showing results for different learning scenarios.

A Math Training Platform to Foster Individual Learning

2017 ◽  
pp. 1-26
Author(s):  
Edgar Neuherz ◽  
Martin Ebner
Keyword(s):  
Individual Learning ◽  
Mobile Technologies ◽  
Daily Lives ◽  
Standard Format ◽  
Learning Platform ◽  
New Information ◽  
New Learning ◽  
Learning Scenarios ◽  
The One ◽  
Future Education

The use of mobile technologies such as Smartphone, Tablet are becoming more pervasive in our daily lives. Obviously, it should also be used and integrated to support learning seamlessly. But not all learning environments can be used with all these devices. In some cases, special libraries are needed (e.g. flash not available on iPad, Mac OS X) or a permanent internet connection to a learning-platform is necessary. This publication proposes a new way in math education using the standard format PDF with completely auto-generated tasks for seamless learning and presents new learning scenarios for collaborations. On the one hand a new information system will be described and on the other hand use cases are carried out to establish individual learning. It can be concluded that individual math training is an important step to foster future education.

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.

Multi-Agent Systems for Distributed Geospatial Modeling, Simulation and Computing

2010 ◽  
pp. 196-204 ◽  
Author(s):  
Genong Yu ◽  
Liping Di ◽  
Wenli Yang ◽  
Peisheng Zhao ◽  
Peng Yue
Keyword(s):  
Intelligent Agents ◽  
Intelligent Agent ◽  
Geospatial Data ◽  
Collective Effects ◽  
Multi Agent Systems ◽  
Geospatial Modeling ◽  
Autonomous Action ◽  
Agent Systems ◽  
Modeling Simulation ◽  
Multi Agent

Multi-agent system is specialized in studying the collective effects of multiple intelligent agents. An intelligent agent is a computer system with autonomous action in an environment. This technology is especially suitable for studying geospatial phenomena since they are complex in nature and call for intertwined actions from different forces. This chapter describes multi-agent systems and their application in geospatial modeling, simulation and computing. Geospatial data integration and mining are discussed.

A New Multiple Intelligent Agents Reasoning Model Based on Fluent Calculus

2013 ◽  
Vol 411-414 ◽  
pp. 2017-2022
Author(s):  
Tao Yang ◽  
Hong Li Deng ◽  
Yong Feng Diao
Keyword(s):  
Intelligent Agents ◽  
Dynamic Environment ◽  
Virtual Agents ◽  
Limited Information ◽  
Virtual Agent ◽  
Model Based ◽  
Intelligent Virtual Agents

In this paper, we discuss the cooperation behaviors of intelligent virtual agents with autonomous and cooperative ability .Based on the theory of fluent calculus, we have designed an agent reasoning model .In this model, intelligent virtual agent could automatically judge the next action in the action queue and constructs the dynamic environment quickly with limited information from sensor. Furthermore, a type of request/server cooperation function has been designed for the cooperation among virtual agents to solve the conflicts and to realize the joint goals. Experiment results obtained demonstrated that intelligent virtual agents could cooperate well by our reasoning model.

The use of intelligent agents in modeling an integrated information system of transport logistics

2020 ◽  
Vol 5 ◽  
pp. 59-66
Author(s):  
Y.M. Iskanderov ◽  
Keyword(s):  
Information System ◽  
Supply Chains ◽  
Intelligent Agents ◽  
Technological Processes ◽  
Transport Services ◽  
Wide Range ◽  
Integrated Information System ◽  
Multi Agent ◽  
Transport Logistics ◽  
Integrated Information

Aim. The use of intelligent agents in modeling an integrated information system of transport logistics makes it possible to achieve a qualitatively new level of design of control systems in supply chains. Materials and methods. The article presents an original approach that implements the possibilities of using multi-agent technologies in the interests of modeling the processes of functioning of an integrated information system of transport logistics. It is shown that the multi-agent infrastructure is actually a semantic shell of the information system, refl ecting the rules of doing business and the interaction of its participants in the supply chains. The characteristic of the model of the class of an intelligent agent, which is basic for solving problems of management of transport and technological processes, is given. Results. The procedures of functioning of the model of integration of information resources of the participants of the transport services market on the basis of intelligent agents are considered. The presented procedures provide a wide range of network interaction operations in supply chains, including traffi c and network structure “fl exible” control, mutual exchange of content and service information, as well as their distributed processing, and information security. Conclusions. The proposed approach showed that the use of intelligent agents in modeling the functioning of an integrated information system makes it possible to take into account the peculiarities of transport and technological processes in supply chains, such as the integration of heterogeneous enterprises, their distributed organization, an open dynamic structure, standardization of products, interfaces and protocols.

scholarly journals Multi-Agent System Observer: Intelligent Support for Engaged E-Learning

Electronics ◽  
2021 ◽  
Vol 10 (12) ◽  
pp. 1370
Author(s):  
Igor Vuković ◽  
Kristijan Kuk ◽  
Petar Čisar ◽  
Miloš Banđur ◽  
Đoko Banđur ◽  
...  
Keyword(s):  
Machine Learning ◽  
Machine Learning Algorithms ◽  
Intelligent Support ◽  
Course Success ◽  
States Of Emergency ◽  
Learning Platform ◽  
Rapid Spread ◽  
E Learning ◽  
Multi Agent ◽  
Observer System

Moodle is a widely deployed distance learning platform that provides numerous opportunities to enhance the learning process. Moodle’s importance in maintaining the continuity of education in states of emergency and other circumstances has been particularly demonstrated in the context of the COVID-19 virus’ rapid spread. However, there is a problem with personalizing the learning and monitoring of students’ work. There is room for upgrading the system by applying data mining and different machine-learning methods. The multi-agent Observer system proposed in our paper supports students engaged in learning by monitoring their work and making suggestions based on the prediction of their final course success, using indicators of engagement and machine-learning algorithms. A novelty is that Observer collects data independently of the Moodle database, autonomously creates a training set, and learns from gathered data. Since the data are anonymized, researchers and lecturers can freely use them for purposes broader than that specified for Observer. The paper shows how the methodology, technologies, and techniques used in Observer provide an autonomous system of personalized assistance for students within Moodle platforms.

EVA 2.0: Emotional and rational multimodal argumentation between virtual agents

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Niklas Rach ◽  
Klaus Weber ◽  
Yuchi Yang ◽  
Stefan Ultes ◽  
Elisabeth André ◽  
...  
Keyword(s):  
Reinforcement Learning ◽  
User Feedback ◽  
Virtual Agents ◽  
Multi Agent System ◽  
Dialogue Game ◽  
Multi Agent ◽  
The Individual ◽  
Minimal Bias ◽  
Intuitive Interface ◽  
Emotional Level

Abstract Persuasive argumentation depends on multiple aspects, which include not only the content of the individual arguments, but also the way they are presented. The presentation of arguments is crucial – in particular in the context of dialogical argumentation. However, the effects of different discussion styles on the listener are hard to isolate in human dialogues. In order to demonstrate and investigate various styles of argumentation, we propose a multi-agent system in which different aspects of persuasion can be modelled and investigated separately. Our system utilizes argument structures extracted from text-based reviews for which a minimal bias of the user can be assumed. The persuasive dialogue is modelled as a dialogue game for argumentation that was motivated by the objective to enable both natural and flexible interactions between the agents. In order to support a comparison of factual against affective persuasion approaches, we implemented two fundamentally different strategies for both agents: The logical policy utilizes deep Reinforcement Learning in a multi-agent setup to optimize the strategy with respect to the game formalism and the available argument. In contrast, the emotional policy selects the next move in compliance with an agent emotion that is adapted to user feedback to persuade on an emotional level. The resulting interaction is presented to the user via virtual avatars and can be rated through an intuitive interface.

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