scholarly journals Why and why notexplanations improve the intelligibility of context-aware intelligent systems

2009 ◽  
Author(s):  
Brian Y. Lim ◽  
Anind K. Dey ◽  
Daniel Avrahami
Keyword(s):  
Intelligent Systems ◽  
Context Aware

Proficiency-aware systems

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Jakob Karolus ◽  
Paweł W. Woźniak
Keyword(s):  
Intelligent Systems ◽  
Adaptive Systems ◽  
Physiological Data ◽  
Context Aware ◽  
Stepping Stone ◽  
Digital World ◽  
Proficiency Estimation ◽  
The Way

Abstract In an increasingly digital world, intelligent systems support us in accomplishing many everyday tasks. With the proliferation of affordable sensing devices, inferring user states from collected physiological data paves the way to tailor-made adaptation. While estimating a user’s abilities is technically possible, such proficiency assessments are rarely employed to benefit the user’s task reflection. In our work, we investigate how to model and design for proficiency estimation as part of context-aware systems. In this paper, we present the definition and conceptual architecture of proficiency-aware systems. The concept is not only applicable to current adaptive systems but provides a stepping stone for systems which actively aid in developing user proficiency during interaction.

A General Context-Aware Framework for Improved Human-System Interactions

AI Magazine ◽  
2015 ◽  
Vol 36 (2) ◽  
pp. 42-49 ◽  
Author(s):  
Stacy Lovell Pfautz ◽  
Gabriel Ganberg ◽  
Adam Fouse ◽  
Nathan Schurr
Keyword(s):  
Intelligent Systems ◽  
Decision Support Tool ◽  
Operational Definition ◽  
Mitigation Strategies ◽  
General Context ◽  
Context Aware ◽  
Support Tool ◽  
Human System ◽  
User Intent ◽  
Challenges And Opportunities

For humans and automation to effectively collaborate and perform tasks, all participants need access to a common representation of potentially relevant situational information, or context. This article describes a general framework for building context-aware interactive intelligent systems that comprises three major functions: (1) capture human-system interactions and infer implicit context; (2) analyze and predict user intent and goals; and (3) provide effective augmentation or mitigation strategies to improve performance, such as delivering timely, personalized information and recommendations, adjusting levels of automation, or adapting visualizations. Our goal is to develop an approach that enables humans to interact with automation more intuitively and naturally that is reusable across domains by modeling context and algorithms at a higher-level of abstraction. We first provide an operational definition of context and discuss challenges and opportunities for exploiting context. We then describe our current work towards a general platform that supports developing context-aware applications in a variety of domains. We then explore an example use case illustrating how our framework can facilitate personalized collaboration within an information management and decision support tool. Future work includes evaluating our framework.

scholarly journals Towards Context-Aware Knowledge Management in e-Enterprises

2005 ◽  
Vol 9 (1) ◽  
pp. 39-45 ◽  
Author(s):  
Weihong Huang ◽  
Keyword(s):  
Knowledge Management ◽  
Intelligent Systems ◽  
Reference Model ◽  
Negative Impact ◽  
Global Network ◽  
Context Aware ◽  
Contextual Knowledge ◽  
Semantic Grid ◽  
Knowledge Grid ◽  
Context Knowledge

To reduce the negative impact of knowledge loss and to improve knowledge reuse effectiveness in knowledge management in e-Enterprises, this paper presents a context-aware approach to facilitate managing various types of static enterprise information and dynamic process information. Proposed approach features representing and integrating information at different conceptual levels to present contextual knowledge in an open environment. In this paper, we redefine the concept of context in intelligent systems and propose a set of meta-information elements for context description in business environments. In realising the context-awareness in knowledge management, we present a context knowledge structure model and look into the corresponding context knowledge storage and reuse solutions. To enhance context-aware knowledge management for e-Businesses over the global network, we introduce a new concept of Context Knowledge Grid with a layered knowledge interoperation reference model, which are supposed to leverage the contextual knowledge in e-Enterprises and enable interoperation with other knowledge frameworks such as the Semantic Web and the Semantic Grid.

On the Design of Multiagent, Context-Aware, and Mobile Systems

2009 ◽  
pp. 357-370 ◽  
Author(s):  
Tagelsir M. Gasmelseid
Keyword(s):  
Software Engineering ◽  
Multiagent Systems ◽  
Context Awareness ◽  
Intelligent Systems ◽  
Mobile Systems ◽  
Service Availability ◽  
Context Aware ◽  
Analysis And Design ◽  
Engineering Practices ◽  
Decision Environments

This chapter addresses the software engineering dimensions associated with the development of mobile and context-aware multiagent systems. It argues that despite the growing deployment of such systems in different application domains little has been done with regards to their analysis and design methodologies. The author argues that the introduction of mobility and context awareness raises three main challenges that deserve a paradigm shift: the challenge of information integrity, service availability on mobile devices, and the complexity of decision modeling. Because they reflect different operational and procedural dimensions, the author argues that the conventional software engineering practices used with intelligent systems that possess other agency qualities need to be “re-engineered.” The chapter emphasizes that the envisioned methodology should reflect a thorough understanding of decision environments, domains epresentation, and organizational and decision-making structures. Furthermore, the chapter provides a description for the appropriate enablers necessary for integrated implementation.

scholarly journals Simulation Methodology-Based Context-Aware Architecture Design for Behavior Monitoring of Systems

Symmetry ◽  
2020 ◽  
Vol 12 (9) ◽  
pp. 1568 ◽  
Author(s):  
Tae Ho Cho
Keyword(s):  
Intelligent Systems ◽  
Discrete Event ◽  
Simulation Models ◽  
Real System ◽  
Problem Solver ◽  
Context Aware ◽  
System Specification ◽  
The Real ◽  
Behavior Monitoring ◽  
Major Application

Generally, simulation models are constructed to replicate and predict the behavior of real systems that currently exist or are expected to exist in the future. Once a simulation model is implemented, the model can be connected to a real system for which the model has been built through sensors or networks so that important activities in the real system can be monitored indirectly through the model. This article proposes a modeling formalism BM-DEVS (Behavior Monitor-DEVS) that defines simulation models capable of monitoring the desired behavior patterns within the models so that the target system’s behavior can be monitored indirectly. In BM-DEVS, an extension of classic Discrete Event System Specification (DEVS), the behavior to be monitored is expressed as a set of temporal logic (TL) production rules within a multi-component model that consists of multiple component models to be monitored. An inference engine module for reasoning with the TL rules is designed based on the abstract simulator that carries out instructions in the BM-DEVS models to perform the simulation process. The major application of BM-DEVS is in the design and implementation of the context-aware architecture needed for various intelligent systems as a core constituent. Essentially all systems where some form of behavior monitoring is required are candidate applications of BM-DEVS. This research is motivated by the view that there exists symmetry between the real-world and the cyber world, in that the problems in both environments should be expressed with the same basic constituents of time and space; this naturally leads to adopting spatiotemporal variables composed of simulation models and developing a problem solver that exploits these variables.

Context-Awareness in Ambient Intelligence

2011 ◽  
pp. 13-23
Author(s):  
Declan Traynor ◽  
Ermai Xie ◽  
Kevin Curran
Keyword(s):  
Human Computer Interaction ◽  
Ubiquitous Computing ◽  
Context Awareness ◽  
Intelligent Systems ◽  
Ambient Intelligence ◽  
Context Aware ◽  
Ethical Challenges ◽  
Electronic Environments ◽  
Computer Interaction

Ambient Intelligence (AmI) deals with the issue of how we can create context-aware, electronic environments which foster seamless human-computer interaction. Ambient Intelligence encompasses the fields of ubiquitous computing, artificially intelligent systems, and context awareness among others. This paper discusses context-awareness and examines how discoveries in this area will be key in propelling the development of true AmI environments. This will be done by examining the background and reasoning behind this particular strand of AmI research along with an overview of the technologies being explored alongside possible applications of context awareness in computing as well as technological and socio- ethical challenges in this field.

scholarly journals A Framework for Exploiting Internet of Things for Context-Aware Trust-Based Personalized Services

2018 ◽  
Vol 2018 ◽  
pp. 1-24 ◽  
Author(s):  
Abayomi Otebolaku ◽  
Gyu Myoung Lee
Keyword(s):  
Internet Of Things ◽  
Intelligent Systems ◽  
User Profile ◽  
Personalized Recommendation ◽  
The Internet ◽  
Context Information ◽  
Context Aware ◽  
Everyday Objects ◽  
Personalized Services

In the last years, we have witnessed the introduction of the Internet of Things (IoT) as an integral part of the Internet with billions of interconnected and addressable everyday objects. On one hand, these objects generate a massive volume of data that can be exploited to gain useful insights into our day-to-day needs. On the other hand, context-aware recommender systems (CARSs) are intelligent systems that assist users to make service consumption choices that satisfy their preferences based on their contextual situations. However, one of the key challenges facing the development and deployment of CARSs is the lack of functionality for providing dynamic and reliable context information required by the recommendation decision process. Thus, data obtained from IoT objects and other sources can be exploited to build CARSs that satisfy users’ preferences, improve quality of experience, and boost recommendation accuracy. This article describes various components of a conceptual IoT-based framework for context-aware personalized recommendations. The framework addresses the weakness whereby CARSs rely on static and limited contexts from user’s mobile phone by providing additional components for reliable and dynamic context information, using IoT context sources. The core of the framework consists of a context classification and reasoning management and a dynamic user profile model, incorporating trust to improve the accuracy of context-aware personalized recommendations. Experimental evaluations show that incorporating context and trust into personalized recommendation process can improve accuracy.

A Review of Cognitive Assistants for Healthcare

2021 ◽  
Vol 53 (6) ◽  
pp. 1-37
Author(s):  
Sarah Masud Preum ◽  
Sirajum Munir ◽  
Meiyi Ma ◽  
Mohammad Samin Yasar ◽  
David J. Stone ◽  
...  
Keyword(s):  
Cognitive Abilities ◽  
Intelligent Systems ◽  
Healthcare Providers ◽  
Design Guidelines ◽  
Context Aware ◽  
Emerging Trends ◽  
Target User ◽  
Characteristic Features ◽  
Definition Of ◽  
Remote Patient

Healthcare cognitive assistants (HCAs) are intelligent systems or agents that interact with users in a context-aware and adaptive manner to improve their health outcomes by augmenting their cognitive abilities or complementing a cognitive impairment. They assist a wide variety of users ranging from patients to their healthcare providers (e.g., general practitioner, specialist, surgeon) in several situations (e.g., remote patient monitoring, emergency response, robotic surgery). While HCAs are critical to ensure personalized, scalable, and efficient healthcare, there exists a knowledge gap in finding the emerging trends, key challenges, design guidelines, and state-of-the-art technologies suitable for developing HCAs. This survey aims to bridge this gap for researchers from multiple domains, including but not limited to cyber-physical systems, artificial intelligence, human-computer interaction, robotics, and smart health. It provides a comprehensive definition of HCAs and outlines a novel, practical categorization of existing HCAs according to their target user role and the underlying application goals. This survey summarizes and assorts existing HCAs based on their characteristic features (i.e., interactive, context-aware, and adaptive) and enabling technological aspects (i.e., sensing, actuation, control, and computation). Finally, it identifies critical research questions and design recommendations to accelerate the development of the next generation of cognitive assistants for healthcare.

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