Towards learning domain-independent planning heuristics

Automated planning remains one of the most general paradigms in Artificial Intelligence, providing means of solving problems coming from a wide variety of domains. One of the key factors restricting the applicability of planning is its computational complexity resulting from exponentially large search spaces. Heuristic approaches are necessary to solve all but the simplest problems. In this work, we explore the possibility of obtaining domain-independent heuristic functions using machine learning. This is a part of a wider research program whose objective is to improve practical applicability of planning in systems for which the planning domains evolve at run time. The challenge is therefore the learning of (corrections of) domain-independent heuristics that can be reused across different planning domains.Comment: Accepted for the IJCAI-17 Workshop on Architectures for Generality and Autonom

Domain Objects and Microservices for Systems Development: a roadmap

This paper discusses a roadmap to investigate Domain Objects being an adequate formalism to capture the peculiarity of microservice architecture, and to support Software development since the early stages. It provides a survey of both Microservices and Domain Objects, and it discusses plans and reflections on how to investigate whether a modeling approach suited to adaptable service-based components can also be applied with success to the microservice scenario

MeetDurian: A Gameful Mobile App to Prevent COVID-19 Infection

The COVID-19 problem has not gone away with the passing of the seasons. Even though most countries have achieved remarkable results in fighting against epidemic diseases and preventing and controlling viruses, the general public is still far from understanding the new crown virus and lacks imagination on its transmission law. In this paper, we propose MeetDurian: a cross-platform mobile application that exploits a location-based game to improve users' hygiene habits and reduce virus dispersal. We present its main features, its architecture, and its core technologies. Finally, we report a set of experiments that prove the acceptability and usability of MeetDurian. An illustrative demo of the mobile app features is shown in the following video: https://youtu.be/Vqg7nFDQuOU.Comment: 4 pages, 4 figure

Dynamic adaptation of service-based applications: a design for adaptation approach

Abstract A key challenge posed by the Next Generation Internet landscape is that modern service-based applications need to cope with open and continuously evolving environments and to operate under dynamic circumstances (e.g., changes in the users requirements, changes in the availability of resources). Indeed, dynamically discover, select and compose the appropriate services in such environment is a challenging task. Self-adaptation approaches represent effective instruments to tackle this issue, because they allow applications to adapt their behaviours based on their execution environment. Unfortunately, although existing approaches support run-time adaptation, they tend to foresee the adaptation requirements and related solutions at design-time, while working under a "closed-world" assumption. In this article our objective is that of providing a new way of approaching the design, operation and run-time adaptation of service-based applications, by considering the adaptivity as an intrinsic characteristic of applications and from the earliest stages of their development. We propose a novel design for adaptation approach implementing a complete lifecycle for the continuous development and deployment of service-based applications, by facilitating (i) the continuous integration of new services that can easily join the application, and (ii) the operation of applications under dynamic circumstances, to face the openness and dynamicity of the environment. The proposed approach has been implemented and evaluated in a real-world case study in the mobility domain. Experimental results demonstrate the effectiveness of our approach and its practical applicability

PolyGloT: A Personalized and Gamified eTutoring System

The digital age is changing the role of educators and pushing for a paradigm shift in the education system as a whole. Growing demand for general and specialized education inside and outside classrooms is at the heart of this rising trend. In modern, heterogeneous learning environments, the one-size-fits-all approach is proven to be fundamentally flawed. Individualization through adaptivity is, therefore, crucial to nurture individual potential and address accessibility needs and neurodiversity. By formalizing a learning framework that takes into account all these different aspects, we aim to define and implement an open, content-agnostic, and extensible eTutoring platform to design and consume adaptive and gamified learning experiences. Adaptive technology supplementing teaching can extend the reach of every teacher, making it possible to scale 1-1 learning experiences. There are many successful existing technologies available but they come with fixed environments that are not always suitable for the targeted audiences of the course material. This paper presents PolyGloT, a system able to help teachers to design and implement a gamified and adaptive learning paths. Through it we address some important issues including the engagement, fairness, and effectiveness of learning environments. We do not only propose an innovative platform that could foster the learning process of different disciplines, but it could also help teachers and instructors in organizing learning material in an easy-access repositoryComment: 6 pages; 5 figure

ATLAS: A new way to exploit world-wide mobility services

Abstract Despite the extent of the ecosystem of mobility services and the disparate functionalities they offer, organizing journeys by properly exploiting them and enhancing their interoperability is still a complex task. Moreover, the high degree of dynamicity characterizing modern service-based systems requires to make them able to self-adapt at runtime. In this paper, we present ATLAS , a world-wide travel assistant able to provide accurate and context-aware traveling solutions, supporting users for the whole travel duration. ATLAS has been realized by exploiting a tool to engineer adaptive by design service-based systems operating in open and dynamic environments

A context-aware framework for dynamic composition of process fragments in the internet of services

Abstract In the last decade, many approaches to automated service composition have been proposed. However, most of them do not fully exploit the opportunities offered by the Internet of Services (IoS). In this article, we focus on the dynamicity of the execution environment, that is, any change occurring at run-time that might affect the system, such as changes in service availability, service behavior, or characteristics of the execution context. We indicate that any IoS-based application strongly requires a composition framework that supports for the automation of all the phases of the composition life cycle, from requirements derivation, to synthesis, deployment and execution. Our solution to this ambitious problem is an AI planning-based composition framework that features abstract composition requirements and context-awareness. In the proposed approach most human-dependent tasks can be accomplished at design time and the few human intervention required at run time do not affect the system execution. To demonstrate our approach in action and evaluate it, we exploit the ASTRO-CAptEvo framework, simulating the operation of a fully automated IoS-based car logistics scenario in the Bremerhaven harbor