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A collective adaptive system is made up of cooperating entities that can adjust in real time to evolving, open environments and shifting requirements. To ensure such a system meets its intended goals, rigorous engineering must employ suitable ...

Online reinforcement learning (RL) is increasingly used for realizing adaptive systems in the presence of design time uncertainty because Online RL can leverage data only available at run time. With Deep RL gaining interest, the learned knowledge is no ...

The Content Improvement Service (CIS) is a platform-level adaptive system that monitors millions of automatically generated formative practice questions that are available to students as a study feature in thousands of textbooks. The CIS was ...

Disturbance observer‐based control method has achieved good results in the car‐following scenario of intelligent and connected vehicle (ICV). However, the gain of conventional extended disturbance observer (EDO)‐based control method is usually ...

The asymptotic optimality of adaptive systems with alternative standards, one of which corresponds to the class of radio engineering structures with an adaptive antenna array, and the other one to the class with an adaptive interference ...

The articulation between machine tutoring and human tutoring remains a productive research within in the context of Intelligent Tutoring Systems (ITS), particularly in the context of e-learning where the dropout rate is high. We explore an innovative ...

Online reinforcement learning is an emerging machine learning approach that addresses the challenge of design-time uncertainty faced when building self-adaptive systems. Online reinforcement learning means that the self-adaptive system can learn from ...

This article introduces a novel sliding mode observer design for sector bounded nonlinear systems. The proposed observer can simultaneously estimate both states and unknown parameters in the presence of disturbances and measurement noise. The ...

Physical distancing measurements are accepted to be critical strategies to slow the spread of COVID-19 disease. Most of the recent works to measure the physical distancing between people aims for easy-to-deploy systems such as contact tracing ...

Human Computer Interaction can be impeded by various interaction obstacles, impacting a user’s perception or cognition. In this work, we detect and discriminate such interaction obstacles from different data modalities to compensate for them through ...

Physical agents that can autonomously generate engaging, life-like behavior will lead to more responsive and user-friendly robots and other autonomous systems. Although many advances have been made for one-to-one interactions in well-controlled settings, ...

Large-scale distributed computing architectures such as, e.g. systems on chip or many-core devices, offer advantages over monolithic or centralised single-core systems in terms of speed, power/thermal performance and fault tolerance. However, these are ...

Tourist recommendation systems have been assisting tourists to select their preferred attractions or destinations based on some specified criteria. However, once a recommendation is made, it is unchanged until the travel plan is executed. Some changes ...

In this paper, we report findings from our pilot study using semi-structured interviews to assess users' perceived receptivity to an adaptive system of engagement strategies, ewrapper, that "wraps" around decision points in a dietary self-monitoring ...

Models are well-defined abstractions that provide cost-effective representations of the real-world for a precise purpose. When dealing with complex problems, there usually exist multiple abstractions, typically describing partially overlapping details ...

The return on investment of a battery system is maximized if the battery control strategy is appropriately matched to the operating environment (e.g., pricing scheme, electrical load). For residential battery systems, the current practice is to ...

Nowadays, society is in constant evolution, which allows constant production of new knowledge. In this way, citizens are constantly pressured to obtain new qualifications through training/requalification. The need for qualified people has been growing ...

We propose a heterogeneous island model where each of the islands can run a different optimization algorithm. The distributed computation is managed by a central planner, that re-plans the methods during the run of the algorithm - less successful ...

A cloud is a distributed Internet-based software system providing resources as tiered services. Through service-orientation and virtualization for resource provisioning, cloud applications can be deployed and managed dynamically. We discuss the building ...