Interface Agent Research Articles

Decision support aids with anthropomorphic characteristics influence trust and performance in younger and older adults

This study examined the use of deliberately anthropomorphic automation on younger and older adults' trust, dependence and performance on a diabetes decision-making task. Research with anthropomorphic interface agents has shown mixed effects in judgments of preferences but has rarely examined effects on performance. Meanwhile, research in automation has shown some forms of anthropomorphism (e.g. etiquette) have effects on trust and dependence on automation. Participants answered diabetes questions with no-aid, a non-anthropomorphic aid or an anthropomorphised aid. Trust and dependence in the aid was measured. A minimally anthropomorphic aide primarily affected younger adults' trust in the aid. Dependence, however, for both age groups was influenced by the anthropomorphic aid. Automation that deliberately embodies person-like characteristics can influence trust and dependence on reasonably reliable automation. However, further research is necessary to better understand the specific aspects of the aid that affect different age groups. Automation that embodies human-like characteristics may be useful in situations where there is under-utilisation of reasonably reliable aids by enhancing trust and dependence in that aid. Practitioner Summary: The design of decision-support aids on consumer devices (e.g. smartphones) may influence the level of trust that users place in that system and their amount of use. This study is the first step in articulating how the design of aids may influence user's trust and use of such systems

Educational interface agents as social models to influence learner achievement, attitude and retention of learning

This study examined the impacts of educational interface agents with different attributes on achievement, attitude and retention of elementary school students in their science and technology courses. The study was implemented in four different eighth- grade classes (aged 13–14) of an elementary school. Four different types of educational software, covering living things and life unit of 8th graders, were developed to analyze the impacts of educational software agents with different attributes on the results of learning. The study was conducted according to experimental model with pretest and posttest control group, which is one of the quasi-experimental designs. For five consecutive weeks experimental and control group students used the software designed for this research. The students were asked to fill an attitude scale on science and technology both before and after the implementation. And following completion, an achievement test was applied. The results of the study revealed that students who used a human-like educational interface agent were more successful than both the rest of the experimental groups and the control group in terms of achievement, attitude and retention of learning in science and technology classes. It is also revealed that the software to be developed for elementary school 8th graders (aged 13–14) should be supported with human-like educational interface agents. ► The impacts of different interface agents on the achievement, attitude and retention. ► Four different educational software were developed. ► Using human-like educational interface agent is better than other agents. ► Educational interface agents have a positive effect on student achievement.

Experimental Investigation of Human Adaptation to Change in Agent's Strategy through a Competitive Two-Player Game

We conducted an experimental investigation on human adaptation to change in an agent's strategy through a competitive two-player game. Modeling the process of human adaptation to agents is important for designing intelligent interface agents and adaptive user interfaces that learn a user's preferences and behavior strategy. However, few studies on human adaptation to such an agent have been done. We propose a human adaptation model for a two-player game. We prepared an on-line experimental system in which a participant and an agent play a repeated penny-matching game with a bonus round. We then conducted experiments in which different opponent agents (human or robot) change their strategy during the game. The experimental results indicated that, as expected, there is an adaptation phase when a human is confronted with a change in the opponent agent's strategy, and adaptation is faster when a human is competing with robot than with another human.

RAEDSS: An integrated decision support system for regional agricultural economy in China

Recent advances in artificial intelligence, particularly in the field of multi-agent system theory and techniques, offer great promises in the development of decision support systems. This paper designs an agent-based regional agricultural economy decision support system (RAEDSS) to deal with complex decision problems. It introduces the architecture of the system, including interface agents, management agents, functional agents, model agents, information agents and knowledge agents and their interactions. Since dynamic analysis, evaluation, forecast, optimization and decision of regional agricultural economy are the central task of RAEDSS, this paper gives a detailed discussion on the decision processes and internal mechanisms in the system. Meanwhile, agent-based modeling is introduced to simulate and evaluate policy impact on rural development in different scenarios as an important part in RAEDSS. The simulation result shows that this agent-based agricultural development model is able to perform regeneration and is able to produce likely-to-occur projections of reality. The related issue such as building an agent based on the theory of classifier systems is also surveyed.

Intermediaries: reflections on virtual humans, gender, and the Uncanny Valley

Embodied interface agents are designed to ease the use of technology. Furthermore, they present one possible solution for future interaction scenarios beyond the desktop metaphor. Trust and believa...

An intelligent tutor for teaching software design patterns

ABSTRACTHow to teach students to design in the classroom? When is experience crucial to do design? In particular, how to teach design patterns to students who are beginning to know the importance of a good design? Experience is essential to understand and apply patterns in an effective way. Generally, novice users are not good at working in real experiences while they are good at learning new techniques and methods for designing. In this work, we show the results of teaching patterns using an artificial intelligent assistant that helps novice developers during the design process. Our assistant is an interface agent that observes novice users working, and when it detects that a design pattern can be applied, it makes a suggestion justifying its opinion. Thus, students understand when and where a pattern could be applied.© 2011 Wiley Periodicals, Inc. Comput Appl Eng Educ 22:583–592, 2014; View this article online at wileyonlinelibrary.com/journal/cae; DOI 10.1002/cae.20582

Assessing the impact of virtual educational interface agents on adults with little or no computer skills

Which characteristics should an interface agent have to ensure it being helpful? An interface agent must make a system effective, efficient and easy to use. The system being developed will help to accomplish this. We consider the most effective ways to present interface agents.

Using agents to improve the usability of the PSP automated tool

Various tools have been produced to assist personal software process (PSP) practitioners in implementing their processes, which require strong discipline from the individual software engineer. Nevertheless, most of the currently available tools still require software engineers to become involved in time-consuming manual processes and offer limited assistance. This research study presents the substantial potential for software agents to be incorporated into PSP automated tools by introducing four new agent-based features. These features are the proactive interface agent, an integrated Gantt chart with sensor-based scheduling, prediction ability and indirect management through multi-agent deployment. This agent has the additional features of flexibility and privacy. Integrated with the proactive assistant, the proposed tools are capable of collecting and processing accurate PSP data metrics and translating them into informative and meaningful information for both the software engineer and the project manager. The use of agents demonstrated in this paper is meant to significantly help engineers to practice all of the PSP processes effectively and in a timely manner and to get feedback on their performance with a visualisation platform at any time.

Modeling sequences of user actions for statistical goal recognition

User goals are of major importance for an interface agent because they serve as a context to define what the user's focus of attention is at a given moment. The user's goals should be detected as soon as possible, after observing few user actions, in order to provide the user with timely assistance. In this article, we describe an approach for modeling and recognizing user goals from observed sequences of user actions by using Variable Order Markov models combined with an exponential moving average (EMA) on the prediction probabilities. The validity of our approach has been tested using data collected from real users in the Unix domain. The results obtained show that an interface agent can achieve near 90% average accuracy and over 58% online accuracy in predicting the most probable user goal after each observed action, in a time linear to the number of goals being modeled. We also found that the use of an EMA allows a faster convergence in the actual user goal.

Personalized detection of user intentions

Interface agents are strategic software components for improving the quality of services to users. In order to be accepted by users, interface agents need to make useful suggestions always in the context of the user’s intention. The user’s intention should be detected as soon as possible so that the agent can define a way to collaborate with the user. Plan recognition can be applied to identify the user’s goal based on his or her actions in the environment. However, classical approaches to plan recognition fail in two main aspects that make them unsuitable for being used by interface agents: the lack of personalization and the lack of consideration of the transition between different goals pursued by the user. We propose an approach to capture intentions taking into account the variables involved in the application domain that represent the user preferences. Experimental evaluations show us that we have found a way for early detection of intentions.

The design of motivational agents and avatars

While the addition of an anthropomorphic interface agent to a learning system generally has little direct impact on learning, it potentially has a huge impact on learner motivation. As such agents become increasingly ubiquitous on the Internet, in virtual worlds, and as interfaces for learning and gaming systems, it is important to design them to optimally impact motivation. The focus of this paper is on the design of agents and avatars (one’s self-representation as a visual agent) for enhancing motivational and affective outcomes, such as improving self-efficacy, engagement and satisfaction, moderating frustration, and/or improving stereotypes. Together with motivational messages and dialogue (which are not discussed here), the agent’s appearance is the most important design feature as it dictates the learner’s perception of the agent as a virtual social model, in the Bandurian sense. The message delivery, through a human-like voice with appropriate and relevant emotional expressions, is also a key motivational design feature. More research is needed to determine the specifics with respect to the ideal agent voice and the role of other nonverbal communication (e.g., deictic gestures) that may contribute to the agent’s role as an embodied motivator, particularly in the long-term.

An active and intelligent network management system with ontology-based and multi-agent techniques

This paper presents a system to collect information through the cooperation of intelligent agent software, in addition to providing warnings after analysis to monitor and predict some possible error indications among controlled objects in the network. This technique derived from the ontology combining Ethereal and Cacti, which store the operating information of network management perfectly into the backend database. The system could sketch the four main components of network management systems with the technique of graphic monitoring multi-agent: an Interface Agent, a Proxy Agent, a Monitoring Agent, and a Search Agent. This architecture can effectively enhance and improve the network monitoring performance to be an active and intelligent network management system. It can present related quantification figures of dynamic information through graphic network monitoring system to provide fast, convenient, and profound network solutions to the users. The experimental outcomes proved that the techniques could not only precisely recognize error alarms but also indeed reduce the recovery time to 61% of traditional processing time for network troubleshooting.

The Initial Construction of a Information Systems Model Response to the Environment Change

This paper studies on the modeling of the changes in the external environment impact on information systems based on complexity theory and multi-Agent theory.In order to establish the model system, This paper gives the Multi-Agent System Model to response the changes of the external environment and studies the unit Agent and interface Agent, which can be used to facilitate follow-up simulation. The model and its simulation system of MIS based on complexity thinking can express the situation of the complex MIS clearly and exactly, reveal its inherent laws, and contribute to the understanding of static and dynamic characteristics. The paper not only studied in informatization theory, but also done some exploration in software and computer application technology, enriched the Multi-agent theory in the area of manufacturing and informatization. Therefore, the model and its simulation system proposed by author is significant for both theory and practice.

Intermediaries: reflections on virtual humans, gender, and the Uncanny Valley

Embodied interface agents are designed to ease the use of technology. Furthermore, they present one possible solution for future interaction scenarios beyond the desktop metaphor. Trust and believability play an important role in the relationship between user and the virtual counterpart. In order to reach this goal, a high degree of anthropomorphism in appearance and behavior of the artifact is pursued. According to the notion of the Uncanny Valley, however, this actually may have quite the opposite effect. This article provides an analysis of the Uncanny Valley effect from a cultural and gender studies perspective. It invites readers to take a closer look at the narratives that influence the production of anthropomorphic artifacts. The article starts with a short introduction of the idea of the Uncanny Valley and gives a brief overview of current artifacts. Following this, a semiotic view on computer science is proposed, which in a further step serves as an epistemological grounding for a gender-critical rereading of the Turing test. This perspective will be supported by analyzing a classic story of user and artifact—E.T.A. Hoffmann’s narration of Olimpia. Finally, the special character of anthropomorphic artifacts is discussed by taking Freud’s concept of “Das Unheimliche”, as well as theories of identity formation into consideration, closing with a plea for a more diverse artifact production.

Conception of the Animated Interface Agent for the Concept Map Based Intelligent Knowledge Assessment System

Conception of the Animated Interface Agent for the Concept Map Based Intelligent Knowledge Assessment SystemThe paper presents the conception of the animated interface agent for the concept map based assessment system. The agent is being developed with an aim to solve problems related to rare use or users' unawareness of functional capabilities of the system. The conception consists of agent's goal, functions, inputs, outputs, embodiment, and properties. It is based on the interface agent characteristics and design requirements summarized in the paper, as well as analysis of system needs.

OntoIAS: An ontology-supported information agent shell for ubiquitous services

This study focused on the development of a core component “information agent shell,” – IAS, applied in general Web systems. We also investigated problems related to the extension of the proposed component in a wide variety of application areas. The shell contains four main components: OntoCrawler, OntoExtractor, OntoClassifier, and OntoRecommender, which are responsible for information searching, information extracting, information classifying, and information representing/ranking, respectively. This system introduced Protégé and relevant APIs to construct the domain ontology and its related ontology services to support all of the operations of the shell that was called OntoIAS. Inside the shell, the proposed method further introduces the ubiquitous interface agent to explore related problems of the ontology-supported information agent shell in ubiquitous environments. The system creates an interaction diagram that both solves the congenital defect problems of mobile equipment and adequately elaborates the powerful functions of backend information systems. In this way, the system can effectively support the basic information requirements of users in ubiquitous environments. The preliminary experimental outcomes can also reveal the basic efficiencies of related sub-systems.

Generic Multimodal Ontologies for Human-Agent Interaction

Watching the evolution of the Semantic Web (SW) from its inception to these days we can easily observe that the main task the developers face while building it is to encode the human knowledge into ontologies and the human reasoning into dedicated reasoning engines. Now, the SW needs to have efficient mechanisms to access information by both humans and artificial agents. The most important tools in this context are ontologies. The last years have been dedicated to solving the infrastructure problems related to ontologies: ontology management, ontology matching, ontology adoption, but as time goes by and these problems are better understood the research interests in this area will surely shift towards the way in which agents will use them to communicate between them and with humans. Despite the fact that interface agents could be bilingual, it would be more efficient, safe and swift that they should use the same language to communicate with humans and with their peers. Since anthropocentric systems entail nowadays multimodal interfaces, it seems suitable to build multimodal ontologies. Generic ontologies are needed when dealing with uncertainty. Multimodal ontologies should be designed taking into account our way of thinking (mind maps, visual thinking, feedback, logic, emotions, etc.) and also the processes in which they would be involved (multimodal fusion and integration, error reduction, natural language processing, multimodal fission, etc.). By doing this it would be easier for us (and also fun) to use ontologies, but in the same time the communication with agents (and also agent to agent talk) would be enhanced. This is just one of our conclusions related to why building generic multimodal ontologies is very important for future semantic web applications.

Autonomic tracing of production processes with mobile and agent-based computing

Tracing items in a supply chain, across different enterprises and through the full processes scope, is today an inherently complex design task. Enterprises are typically comprised of hundreds of applications that are custom built at different times, acquired from third parties and parts of legacy systems, and also operating in multiple tiers of different manufacturing and information system platforms. Further, traceability is characterized by a goal-oriented approach, in which business-process analyses are driven by goal achievements rather than by systematic engineering processes. The use of a classical enterprise integration approach mostly needs tailoring to different applications. Due to the number and diversity of the systems and of their interactions, and to their dynamicity, it is difficult, costly, and therefore often not convenient to develop in large scale distributed systems. To overcome these issues, a supply chain traceability system with a high level of automation is discussed in this paper. In particular, the system adopts an agent-based approach, in which cooperative software agents find solutions to back-end tracing problems by self-organization. Such cooperative agents are based on a business process aware traceability model, and on a service-oriented composition paradigm. Furthermore, an interface agent assists each user to carry out the front-end tracking activities. Interface agents rely on the context-awareness paradigm to gain self-configurability and self-adaptation of the user interface, and on ubiquitous computing technology, i.e., mobile devices and radio-frequency identification, to perform agile and automatic lot identification. The paper comprises real-world experiences on the fashion supply chain.

Personalization of Web Browsing for Novice Users

This paper discusses primary design issues of an intelligent browser for novice users. This work focuses on the study of intelligent interface agents which adapt to the user according to the interactions between the user and the browser. We propose a personal web browser which adapts to the user interface layout and navigation. Adaptation of user interface is associated with including both layout and functionality to the user’s ability and preference but generally keeping consistency. Adaptation to navigation on the other hand refers to personalization of web pages so as to provide personalized information space.

Formulating a Security Layer of Cloud Data Storage Framework Based on Multi Agent System Architecture

The tremendous growth of the cloud computing environments requires new architecture for security services. In addition, these computing environments are open, and users may be connected or disconnected at any time. Cloud Data Storage, like any other emerging technology, is experiencing growing pains. It is immature, it is fragmented and it lacks standardization. To verify the correctness, integrity, confidentially and availability of users’ data in the cloud, we propose a security framework. This security framework consists of two main layers as agent layer and cloud data storage layer. The propose MAS architecture includes five types of agents: UserInterface Agent (UIA), User Agent (UA), DER Agent (DERA), Data Retrieval Agent (DRA) and Data Distribution Preparation Agent (DDPA). The main goal of this paper is to formulate our secure framework and its architecture.