Search results

An intelligent agent‐based information warfare advisor is being developed for the Strategic Crisis Exercise at the US Army War College. This paper will provide some background on intelligent agents and will then describe the proposed architecture for building this intelligent agent‐based information warfare (IW) advisor (called “Bob‐in‐a‐box” ‐ named after our IW domain expert, Bob Minehart).

The purpose of this paper is to present a brief outline of the potential applications of intelligent agent technology in libraries with a list of illustrative examples.

A definition and the attributes of intelligent agents are presented, along with different types of agents and their wide‐ranging applications in various contexts. Illustrative examples of intelligent agents are presented, with some interesting case studies from different domains.

The role of intelligent agents in modern libraries is highlighted from various perspectives, such as electronic information services, collection development and acquisition, classification and organization of library materials, indexing and abstracting, issuing collection, and reference services.

The authors do not attempt to devise an intelligent agent to test these applications in the libraries where they work, although they wish to pursue it as a future course of action.

With libraries dealing with patrons who never disclose fully their information needs and research interests to library staff, libraries have to resort to newer methods of feedback collection, and intelligent agents provide viable options to improve information organization and refine library services.

The paper, being very precise and covering the latest developments, offers new insight into the field of intelligent agents and their pragmatic applications in libraries to interested professionals.

This paper explores a different approach to evaluating the merits of specific technical components of computer based learning applications. A traditional double blind experimental study was implemented in a new context. A computer based Clinical Decision Simulator (CDS) system was designed and implemented incorporating an intelligent agent. This was compared to an otherwise identical system with no agent, and a group of students not using CBL systems. The results suggested that although no improvement in measurable learning outcomes could be conclusively demonstrated there was some evidence that those students using the intelligent agent system demonstrated more positive learning experiences and a deeper conceptualisation of the issues. This would suggest that a comparative multimethod experimental evaluation strategy, although complex (and not without its shortcomings) may help provide a more comprehensive analysis of students learning experience, and provide a useful picture of the student’s perceptions of CBL tools. This novel approach may be of particular relevance where the justification of a specific technological aspect of an e‐learning application is required. The value of developing and using an experimental strategy to evaluate a specific technological aspect of a computer based learning (CBL) application is discussed.

This paper aims to improve understanding of the process through which knowledge acquisition, technical tools and organisation actors can contribute to an organisation development in developing knowledge as a systemic competitive weapon. It examines the relationships between the technology and human value, because they are vital instruments of the knowledge management (KM) process. By considering that KM is related to intelligent agents, information technology (IT), and strategic decision‐support systems (SDSS), it attempts to provide useful insights on KM efficiency. A conceptual model of KM efficiency in the organisations supported by the combination of intelligent agents’ role and intelligent systems resources is presented. The model is divided in two areas: the area of technical tools for specification of intelligent systems resources and the area of intelligent agents destined to focus their roles on organisations’ performance. The major factors are discussed and directions for future research are suggested.

This paper aims to describe the deployment of an e‐learning environment for construction courses based on enhancing virtual computing technologies using agent‐based techniques.

This research involves designing and deploying a complex application that combines advanced visualisation, interactive management through complex virtual devices, distributed multi‐user communication and intelligent components. The proposed agent‐oriented methodology and resulting application organises construction knowledge into a structure that enables the students to undertake more self‐directed, systematic and scientific exploration.

There is great potential for experimenting with a wider variety of educational technologies such as “intelligent” virtual environments. This is a concept that needs further experimentation within construction courses to enrich students' learning with practice‐based experiences. The use of ageny‐oriented objects within simulations and modeling make the virtual learning environment a highly interactive experience. Attempts to do this using traditional intelligent tutoring systems have been frustrated by integrations challenges. Agent‐based systems can handle such challenges. The agent approach is also more efficient in analysing the impact of different decisions in various scenarios by automating the execution of repetitive, time‐consuming actions.

This research identifies specific gaps in the existing e‐learning infrastructure that can be addressed using the intelligent agent paradigm. In particular, the research demonstrates how the notion of learning by actively exploring and controlling environmental variables can be best utilised in the selected domain by giving the learners the means to rapidly visualize the effects of their decisions.

Construction disciplines have increasingly embraced the use of advanced visualisation applications and display systems that allow students to gain a better understanding of the construction process and the resulting facility's performance. Existing efforts are based on image visualisation or animation detailed using, for example, Virtual Reality Modeling Language and 3D Studio Max‐based design animations and walkthroughs. None of these efforts has explored the use of an agent oriented, virtual tutoring approach. A comprehensive literature review established that of no formalised methodologies exist for deploying agent‐based virtual learning environments.

We describe a new approach to intelligent building systems, that utilises an intelligent agent approach to autonomously governing the building environment. We discuss the role of learning in building control systems, and contrast this approach with existing IB solutions. We explain the importance of acquiring information from sensors, rather than relying on pre‐programmed models, to determine user needs. We describe how our architecture, consisting of distributed embedded agents, utilises sensory information to learn to perform tasks related to user comfort, energy conservation, safety and monitoring functions. We show how these agents, employing a behaviour‐based approach derived from robotics research, are able to continuously learn and adapt to individuals within a building, while always providing a fast, safe response to any situation. Finally, we show how such a system could be used to provide support for older people, or people with disabilities, allowing them greater independence and quality of life.

The paper aims to explain the limitations of existing cognitive architectures and affective models, and propose a new cognitive-affective architecture that can be integrated in real intelligent agents to make them more realistic and believable.

The paper evaluates the state of the art, and describes the design and implementation of the cognitive-affective architecture in an agent. A brief evaluation of the agent is provided.

The paper clearly states that it is possible to use cognitive architectures to help, but there is a lack of architectures that address the problem of combining cognition and emotion in agents in a unified, simplified way. A cognitive-affective architecture is useful to make believable intelligent agents in an easier way.

The paper does not explore a lot of possible future work that can be done to extend the emotional expressions of the agent, as well as including direct emotional-sensing capabilities in real time.

The paper argues about the need to include cognitive-affective architectures in modern intelligent agents. The architecture allows to influence and modify the behavior of the agent in real time, to achieve a more realistic and believable interaction with the user.

The paper remarks the importance of a cognitive-affective architecture that makes intelligent agents able to help the users in different tasks and environments.

The paper describes a new cognitive-affective architecture and its utility for modern intelligent agents. This is proven by including it in a previous agent, which boosts its behavior and emotional expression possibilities and thus improves user experience.

The smart open house provides optimal adaptability using sensing, operating, information, and communications technology, in conjunction with open building in-filled components, to perceive user needs and environmental changes, and thereby meet the needs for sustainability and a healthy living environment. These needs are particularly pressing in view of the aged society that will emerge in Taiwan after 2020. Based on the smart open house hypothesis, this study proposes using agent-based smart skins in a smart open house, where an agent-based smart skin is embedded in a lifetime home (or ageless home) with an open system construction. The agent-based smart skin operating mechanism employs fuzzy logic inference and neuro-fuzzy learning to process environmental information from sensing devices and drive skin elements, achieving adaptive action, meeting residents' lifetime use needs, and offering a user experience-oriented smart care capability.

In a previous paper (Nardi & O'Day 1996), we chose to begin thinking about intelligent software agents with a detailed look at what human agents do. Our interest is in agents that provide expert services to end users. We analysed data from two studies of reference librarians to see how they provide value to their clients, considering the librarians as exemplary human agents. Shneiderman (1995) observes that claims about intelligent software agents are vague, dreamy and unrealised: we wanted to bring some precision and optimistic realism to the discussion.

With the development of machine learning techniques, the artificial intelligence systems such as crowd networks are becoming more autonomous and smart. Therefore, there is a growing demand for developing a universal intelligence measurement so that the intelligence of artificial intelligence systems can be evaluated. This paper aims to propose a more formalized and accurate machine intelligence measurement method.

This paper proposes a quality–time–complexity universal intelligence measurement method to measure the intelligence of agents.

By observing the interaction process between the agent and the environment, we abstract three major factors for intelligence measure as quality, time and complexity of environment.

This paper proposes a calculable universal intelligent measure method through considering more than two factors and the correlations between factors which are involved in an intelligent measurement.