Adaptive systems: from intelligent tutoring to autonomous agents

Computer systems which can automatically alter aspects of their functionality or interface to suit the needs of individuals or groups of users have appeared over the years in a variety of guises. Most recently, attention has focused on intelligent interface agents, which are seen as specialised, knowledge-based systems acting on behalf of the user in some aspect of the interaction. Similar requirements for automatic adaptation have been noted in intelligent tutoring systems, natural-language systems and intelligent interfaces. The paper brings together the research which has emanated from a number of backgrounds, and provides a unifying perspective on adaptive systems in general. An architecture for adaptive systems and a methodology for their development are presented. The paper also describes software support for producing adaptive systems, and offers some experimental evidence to justify both the desirability and feasibility of exploiting an adaptive system approach to human-computer interaction     

User modelling for adaptive computer systems: a survey of recent developments

User modelling is becoming an important sub-area of Artificial Intelligence with both theoretical and practical consequences. The theoretical foundations of user modelling are to be found in key areas of AI, such as knowledge representation and plan recognition, while its practical applications impinge on the construction of intelligent user interfaces and adaptive systems. This paper provides a survey of current work in user modelling. The paper begins by distinguishing between AI approaches, which are the subject of this survey, and those of HCI (Human-Computer Interaction) and then considers the major issues in user modelling such as: types of user modelling system, the sorts of information modelled, how the information is acquired, represented and used. The paper concludes by examining some of the more problematic aspects of user modelling as well as indicating areas for future research.     

User-centered approach to adaptive interfaces

Both adaptive and adaptable user interfaces are intended to fit the needs of individual users and their tasks better. A problem with these interfaces is that users must have and use additional knowledge, either to understand the automatic, system-driven adaptations or to adapt the interface on their own. Beyond these two extreme approaches, an automatically self-adapting system and a user manually adapting the system, the approach introduced in this paper strives for a third option, in which users are able to tell the system how to adapt itself. Accordingly, methods include adaptive adaptation (i.e. modifying the adaptation strategies) and implicit adaptation (i.e. changing the underlying models). The applicability of these findings is illustrated in the context of an adaptive action prompting environment.     

Adaptive hypertext navigation based on user goals and context

Hypertext systems allow flexible access to topics of information, but this flexibility has disadvantages. Users often become lost or overwhelmed by choices. An adaptive hypertext system can overcome these disadvantages by recommending information to users based on their specific information needs and preferences. Simple associative matrices provide an effective way of capturing these user preferences. Because the matrices are easily updated, they support the kind of dynamic learning required in an adaptive system.HYPERFLEX, a prototype of an adaptive hypertext system that learns, is described. Informal studies with HYPERFLEX clarify the circumstances under which adaptive systems are likely to be useful, and suggest that HYPERFLEX can reduce time spent searching for information by up to 40%. Moreover, these benefits can be obtained with relatively little effort on the part of hypertext authors or users.The simple models underlying HYPERFLEX's performance may offer a general and useful alternative to more sophisticated modelling techniques. Conditions under which these models, and similar adaptation techniques, might be most useful are discussed.     

Tailoring Automatically Generated Hypertext

This paper describes an approach for tailoring the content and structure of automatically generated hypertext. The implemented system HYLITE is based on applied Natural Language Generation (NLG) techniques, a re-usable user modelling component (VIEWGEN), and a flexible architecture with module feedback. The user modelling component is used by the language generation modules to adapt the hypertext content and links to user beliefs and preferences and to the previous interaction. Unlike previous adaptive NLG systems, which have their own, application-specific user models, HYLITE has re-used a generic agent modelling framework (VIEWGEN) instead. Apart from avoiding the development costs of a new model, this also enabled a more extendable system architecture. Another distinct feature of our approach is making NLG techniques adaptable by the user, i.e., providing users with control over the user model and the hypertext adaptivity.     

Design and evaluation of an adaptive icon toolbar

As information systems become increasingly important in many different domains, the potential to adapt them to individual users and their needs also becomes more important. Adaptive user interfaces offer many possible ways to adjust displays and improve procedures for a user's individual patterns of work. This paper describes an attempt to design an adaptive user interface in a computer environment familiar to many users. According to one classification of adaptive user interfaces, the adaptive bar described in this paper would be classified as a user-controlled self-adaptation system.At the user's convenience, the adaptive bar offers suggestions for adding or removing command icons, based on the frequency and probability of specific commands. It also implements these changes once the user has agreed to them. Beyond the adaptive bar, the general behavior of the whole user interface does not change, thereby allowing the user to maintain a clear general model of the system. This paper describes the decision-making algorithm implemented in the bar. It also describes the bar's self-adaptive behavior of displaying the frequency of each icon's use through the icon's size. Finally, we present some encouraging preliminary results of evaluations by users.     

Adaptive control of a class of nonlinear time-varying systems with multiple models

The adaptive control of nonlinear systems that are linear in the unknown but time-varying parameters are treated in this paper. Since satisfactory transient performance is an important factor, multiple models are required as these parameters change abruptly in the parameter space. In this paper we consider both the multiple models with switching and tuning methodology as well as multiple models with second level adaptation for this class of systems. We demonstrate that the latter approach is better than the former.     

From user interface design to the support of intelligent and adaptive interfaces: an overhaul of user interface software infrastracture

Research on adaptive interfaces in the past has lacked support from user interface tools which allow interfaces to be easily created and modified. Also, current user interface tools provide no support for user models which can collect task-oriented information about users. Developing an adaptive interface requires a user model and an adaptation strategy. It also, however, requires a user interface which can be adapted. The latter task is often time-consuming, especially in relation to more sophisticated user interfaces.

The paper presents a user interface design environment, UIDE, which has a different software infrastracture. Designers use high-level specifications to create a model of an application and links from the application to various interface components. The model is the heart of all the design and run-time support in UIDE, including automatic dialog sequencing and help generation. UIDE provides automatic support for collecting task-oriented information about users, by the use of its high-level specifications in its application model as a basic construct for a user model. Some examples of adaptive interfaces and adaptive help are presented that use the information that is collectable in UIDE.     

An overview of Dynamic Software Product Line architectures and techniques: Observations from research and industry

Over the last two decades, software product lines have been used successfully in industry for building families of systems of related products, maximizing reuse, and exploiting their variable and configurable options. In a changing world, modern software demands more and more adaptive features, many of them performed dynamically, and the requirements on the software architecture to support adaptation capabilities of systems are increasing in importance. Today, many embedded system families and application domains such as ecosystems, service-based applications, and self-adaptive systems demand runtime capabilities for flexible adaptation, reconfiguration, and post-deployment activities. However, as traditional software product line architectures fail to provide mechanisms for runtime adaptation and behavior of products, there is a shift toward designing more dynamic software architectures and building more adaptable software able to handle autonomous decision-making, according to varying conditions. Recent development approaches such as Dynamic Software Product Lines (DSPLs) attempt to face the challenges of the dynamic conditions of such systems but the state of these solution architectures is still immature. In order to provide a more comprehensive treatment of DSPL models and their solution architectures, in this research work we provide an overview of the state of the art and current techniques that, partially, attempt to face the many challenges of runtime variability mechanisms in the context of Dynamic Software Product Lines. We also provide an integrated view of the challenges and solutions that are necessary to support runtime variability mechanisms in DSPL models and software architectures.     

Model-Driven Interactive System Design for Therapy Robots

Physiotherapy using intelligent robots is emerging as a new approach to recovery for many stroke patients. Although therapy robots have a strong potential in dealing with therapeutic and other medical applications, they have not been fully utilized in everyday therapy activities due to concerns over safety and the lack of friendly robot user/patient interaction models. From the viewpoint of software engineering, a user-centred design based on UML (Unified Modelling Language) has been known to be one of the best solutions to satisfy usability since the design process relies heavily on the analysis of users and their tasks to reach their goals. Therefore, a model-driven approach to interactive system design via UML for therapy robots is needed to make them usable in the real world. This paper proposes such approach and introduces a new graphical notation that describes user interface elements and the methods of connection with hardware/software objects. With the proposed abstract interaction models, prototyping interactive systems can be made faster and allows for their evaluation by users and system developers before implementation in order to improve usability from the perspectives of users and system developers.     

人机界面自适应机制的设计和实现

当前，自适应界面已成为人机界面研究的一个方向。首先介绍了有关自适应界面的一些基本概念，并在此基础上提出了一个人机界面的自适应机制。对该机制的系统结构、实现技术进行了广泛的讨论，该机制已被应用于集成化ＣＡＤ／ＣＡＰＰ／ＣＡＭ系统－ＧＳ－ＩＣＣＣ的研制工作中。同时介绍了该机制的一些实现细节。ＧＳ－ＩＣＣＣ的自适应机制已在Ｘ－Ｗｉｎｄｏｗｓ／Ｍｏｔｉｆ环境下实现，并被证明其在提高人机交互有效性上具有良发     

面向Internet的个性化智能信息检索

文中提出了一个面向Ｉｎｔｅｒｎｅｔ的个性化智能信息检索系统,该系统的研究内容属目前智能信息检索领域的重要研究课题。系统采用分布式智能体Ａｇｅｎｔ技术、相关反馈学习算法和基于多用户个性化模式的层次智能信息滤波算法,并采用多模块之间尖线交互机制和个性化检索与集中游览相结合的检索方式等方法,有效地解决了现有系统在交互方式、自适应用户兴趣和信息源的变化、高效并行检索等方面的不足,该系统普通适用于Ｉｎｔｅｒ     

User modelling and user adapted interaction in an intelligent tutoring system

User modelling and user-adapted interaction are crucial to the provision of true individualised instruction, which intelligent tutoring systems strive to achieve. This paper presents how user (student) modelling and student adapted instruction is achieved in FITS, an intelligent tutoring system for the fractions domain. Some researchers have begun questioning both the need for detailed student models as well as the pragmatic possibility of building them. The key contributions of this paper are in its attempt to rehabilitate student modelling/adaptive tutoring within ITSs and in FITS's practical use of simple techniques to realise them with seemingly encouraging results; some illustrations are given to demonstrate the latter.     

自适应笔式用户界面开发的概念框架

提出了一个指导自适应笔式用户界面开发的概念框架CFAPUI(a conceptual framework for developing adaptive pen-based user interface).该框架详细描述了自适应笔式用户界面的软件体系结构,阐述了自适应笔式用户界面的软件体系结构中的各组成模块及其相互间的关系.同时,在体系结构的基础上提出自适应笔式用户界面开发时的具体过程步骤和方法,并通过一个笔式表单应用来说明该开发框架在指导自适应笔式用户界面开发中的具体应用.     

Student modelling in intelligent tutoring systems

Student modelling is a special type of user modelling which is relevant to the adaptability of intelligent tutoring systems. This paper reviews the basic techniques which have been used in student modelling and discusses issues and approaches of current interest. The role of a student model in a tutoring system and methods for representing information about students are discussed. The paper concludes with an overview of some unresolved issues and problems in student modelling.Electric Brain Company     

Toward intelligent data warehouse mining: An ontology-integrated approach for multi-dimensional association mining

A data warehouse is an important decision support system with cleaned and integrated data for knowledge discovery and data mining systems. In reality, the data warehouse mining system has provided many applicable solutions in industries, yet there are still many problems causing users extra problems in discovering knowledge or even failing to obtain the real and useful knowledge they need. To improve the overall data warehouse mining process, we present an intelligent data warehouse mining approach incorporated with schema ontology, schema constraint ontology, domain ontology and user preference ontology. The structures of these ontologies are illustrated and how they benefit the mining process is also demonstrated by examples utilizing rule mining. Finally, we present a prototype multidimensional association mining system, which with intelligent assistance through the support of the ontologies, can help users build useful data mining models, prevent ineffective pattern generation, discover concept extended rules, and provide an active knowledge re-discovering mechanism.     

Teallach: a model-based user interface development environment for object databases

Model-based user interface development environments show promise for improving the productivity of user interface developers, and possibly for improving the quality of developed interfaces. While model-based techniques have previously been applied to the area of database interfaces, they have not been specifically targeted at the important area of object database applications. Such applications make use of models that are semantically richer than their relational counterparts in terms of both data structures and application functionality. In general, model-based techniques have not addressed how the information referenced in such applications is manifested within the described models, and is utilised within the generated interface itself. This lack of experience with such systems has led to many model-based projects providing minimal support for certain features that are essential to such data intensive applications, and has prevented object database interface developers in particular from benefiting from model-based techniques. This paper presents the Teallach model-based user interface development environment for object databases, describing the models it supports, the relationships between these models, the tool used to construct interfaces using the models and the generation of Java programs from the declarative models. Distinctive features of Teallach include comprehensive facilities for linking models, a flexible development method, an open architecture, and the generation of running applications based on the models constructed by designers.     

基于比例公平的多用户MIMO-OFDM系统自适应资源分配算法*

针对传统多用户MIMO-OFDM系统中自适应资源分配算法计算复杂度较高、实时性不强、无法保证用户间公平性等问题,提出了一种低复杂度的自适应子载波、比特及功率分配算法。在子载波分配上,该算法能够在兼顾比例速率约束的前提下使系统发射功率达到最小化;在比特及功率分配上,该算法将非线性优化问题转换为线性优化问题,在保证系统性能的同时显著降低计算量。仿真结果表明,该算法具有良好的性能,能够有效降低计算量,并使系统容量在用户间分配得更加公平和合理。