Multi-Armed Bandits for Intelligent Tutoring Systems

We present an approach to Intelligent Tutoring Systems which adaptively personalizes sequences of learning activities to maximize skills acquired by students, taking into account the limited time and motivational resources. At a given point in time, the system proposes to the students the activity which makes them progress faster. We introduce two algorithms that rely on the empirical estimation of the learning progress, RiARiT that uses information about the difficulty of each exercise and ZPDES that uses much less knowledge about the problem. The system is based on the combination of three approaches. First, it leverages recent models of intrinsically motivated learning by transposing them to active teaching, relying on empirical estimation of learning progress provided by specific activities to particular students. Second, it uses state-of-the-art Multi-Arm Bandit (MAB) techniques to efficiently manage the exploration/exploitation challenge of this optimization process. Third, it leverages expert knowledge to constrain and bootstrap initial exploration of the MAB, while requiring only coarse guidance information of the expert and allowing the system to deal with didactic gaps in its knowledge. The system is evaluated in a scenario where 7-8 year old schoolchildren learn how to decompose numbers while manipulating money. Systematic experiments are presented with simulated students, followed by results of a user study across a population of 400 school children

Engineering Adaptive Model-Driven User Interfaces for Enterprise Applications

Enterprise applications such as enterprise resource planning systems have numerous complex user interfaces (UIs). Usability problems plague these UIs because they are offered as a generic off-the-shelf solution to end-users with diverse needs in terms of their required features and layout preferences. Adaptive UIs can help in improving usability by tailoring the features and layout based on the context-of-use. The model-driven UI development approach offers the possibility of applying different types of adaptations on the various UI levels of abstraction. This approach forms the basis for many works researching the development of adaptive UIs. Yet, several gaps were identified in the state-of-the-art adaptive model-driven UI development systems. To fill these gaps, this thesis presents an approach that offers the following novel contributions: - The Cedar Architecture serves as a reference for developing adaptive model-driven enterprise application user interfaces. - Role-Based User Interface Simplification (RBUIS) is a mechanism for improving usability through adaptive behavior, by providing end-users with a minimal feature-set and an optimal layout based on the context-of-use. - Cedar Studio is an integrated development environment, which provides tool support for building adaptive model-driven enterprise application UIs using RBUIS based on the Cedar Architecture. The contributions were evaluated from the technical and human perspectives. Several metrics were established and applied to measure the technical characteristics of the proposed approach after integrating it into an open-source enterprise application. Additional insights about the approach were obtained through the opinions of industry experts and data from real-life projects. Usability studies showed the approach’s ability to significantly improve usability in terms of end-user efficiency, effectiveness and satisfaction

Pervasive computing at tableside : a wireless web-based ordering system

Purpose &ndash; The purpose of this paper is to introduce a wireless web-based ordering system called iMenu in the restaurant industry. Design/methodology/approach &ndash; By using wireless devices such as personal digital assistants and WebPads, this system realizes the paradigm of pervasive computing at tableside. Detailed system requirements, design, implementation and evaluation of iMenu are presented.Findings &ndash; The evaluation of iMenu shows it explicitly increases productivity of restaurant staff. It also has other desirable features such as integration, interoperation and scalability. Compared to traditional restaurant ordering process, by using this system customers get faster and better services, restaurant staff cooperate more efficiently with less working mistakes, and enterprise owners thus receive more business profits. Originality/value &ndash; While many researchers have explored using wireless web-based information systems in different industries, this paper presents a system that employs wireless multi-tiered web-based architecture to build pervasive computing systems. Instead of discussing theoretical issues on pervasive computing, we focus on practical issues of developing a real system, such as choosing of web-based architecture, design of input methods in small screens, and response time in wireless web-based systems.<br /

From supply chains to demand networks. Agents in retailing: the electrical bazaar

A paradigm shift is taking place in logistics. The focus is changing from operational effectiveness to adaptation. Supply Chains will develop into networks that will adapt to consumer demand in almost real time. Time to market, capacity of adaptation and enrichment of customer experience seem to be the key elements of this new paradigm. In this environment emerging technologies like RFID (Radio Frequency ID), Intelligent Products and the Internet, are triggering a reconsideration of methods, procedures and goals. We present a Multiagent System framework specialized in retail that addresses these changes with the use of rational agents and takes advantages of the new market opportunities. Like in an old bazaar, agents able to learn, cooperate, take advantage of gossip and distinguish between collaborators and competitors, have the ability to adapt, learn and react to a changing environment better than any other structure. Keywords: Supply Chains, Distributed Artificial Intelligence, Multiagent System.Postprint (published version

WLAN Hot Spot services for the automotive and oil industries :a business analysis Or : "Refuel the car with petrol and information, both ways at the gas station"

While you refuel for gas ,why not refuel for information or download vehicle data ? This paper analyzes in extensive detail the user segmentation by vehicle usage , service offering , and full business models from WLAN hot spot services delivered to vehicles (private, professional , public) around gas stations . Are also analyzed the parties which play a role in such service authorization, provisioning and delivery , with all the dependencies modelled by attributed digraphs . Sevice planning is included as to WLAN base station capabilities . Five year financial models (CAPEX,OPEX) , and data pertain to two possible service suppliers : multi-service oil companies, and mobile service operators (or MVNO) . Model optimization on the return-on-investment (ROI) is carried out for different deployment scenarios ,geographical coverage assumptions, as well as tariff structures . Comparison is also being made with public GPRS data services ,as precursors for 3G services,and the effect of WLAN roaming is analyzed .Analysis shows that due to manpower costs and marketing costs , suitable ROI will not be achieved unless externalities are accounted for and innovative tariff structures are introduced . Open issues and further research are outlined . Further work is carried out,also with automotive electronics sector , wireless systems providers , wireless terminals platform suppliers , and vehicle manufacturers .WLAN services;WLAN;business models;fuel stations;mobile operator;oil company;professional vehicles

RBUIS: simplifying enterprise application user interfaces through engineering role-based adaptive behavior

Enterprise applications such as customer relationship management (CRM) and enterprise resource planning (ERP) are very large scale, encompassing millions of lines-of-code and thousands of user interfaces (UI). These applications have to be sold as feature-bloated off-the-shelf products to be used by people with diverse needs in required feature-set and layout preferences based on aspects such as skills, culture, etc. Although several approaches have been proposed for adapting UIs to various contexts-of-use, little work has focused on simplifying enterprise application UIs through engineering adaptive behavior. We define UI simplification as a mechanism for increasing usability through adaptive behavior by providing users with a minimal feature-set and an optimal layout based on the context-of-use. In this paper we present Role-Based UI Simplification (RBUIS), a tool supported approach based on our CEDAR architecture for simplifying enterprise application UIs through engineering role-based adaptive behavior. RBUIS is integrated in our general-purpose platform for developing adaptive model-driven enterprise UIs. Our approach is validated from the technical and end-user perspectives by applying it to developing a prototype enterprise application and user-testing the outcome