Aldo Franco Dragoni

Exploring the ambient assisted living domain: a systematic review

AbstractAmbient assisted living (AAL) is focused on providing assistance to people primarily in their natural environment. Over the past decade, the AAL domain has evolved at a fast pace in various directions. The stakeholders of AAL are not only limited to patients, but also include their relatives, social services, health workers, and care agencies. In fact, AAL aims at increasing the life quality of patients, their relatives and the health care providers with a holistic approach. This paper aims at providing a comprehensive overview of the AAL domain, presenting a systematic analysis of over 10 years of relevant literature focusing on the stakeholders’ needs, bridging the gap of existing reviews which focused on technologies. The findings of this review clearly show that until now the AAL domain neglects the view of the entire AAL ecosystem. Furthermore, the proposed solutions seem to be tailored more on the basis of the available existing technologies, rather than supporting the various stakeholders’ needs. Another major lack that this review is pointing out is a missing adequate evaluation of the various solutions. Finally, it seems that, as the domain of AAL is pretty new, it is still in its incubation phase. Thus, this review calls for moving the AAL domain to a more mature phase with respect to the research approaches.

Belief Revision Through the Belief-Function Formalism in a Multi-Agent Environment

The abilities of detecting contradictions and rearranging the cognitive space in order to cope with them are important to be embedded in the BDI architecture of an agent acting in a complex and dynamic world. However, to be accomplished in a multi-agent environment, “belief revision” must depart considerably from its original definitions. According to us, the main changes should be the following ones: 1. replacing the “priority to the incoming information principle” with the “recoverability principle”: any previously believed piece of information must belong to the current cognitive state whenever it is possible 2. dealing not just with pieces of information but with couples since the reliability of the source affects the credibility of the information and vice-versa.

Distributed Belief Revision

In this paper, a distributed approach to belief revision is presented. It is conceived as a collective activity of a group of interacting agents, in which each component contributes with its own local beliefs. The integration of the different opinions is performed not by an external supervisor, but by the entire group through an election mechanism. Each agent exchanges information with the other components and uses a local belief revision mechanism to maintain its cognitive state consistent. We propose a model for local belief revision/integration based on what we called: “Principle of Recoverability.” Computationally, our way to belief revision consists of three steps acting on the symbolic part of the information, so as to deal with consistency and derivation, and two other steps working with the numerical weight of the information, so as to deal with uncertainty. In order to evaluate and compare the characteristics and performance of the centralized and of the distributed approaches, we made five different experiments simulating a simple society in which each agent is characterized by a degree of competence, communicates with some others, and revise its cognitive state. The results of these experiments are presented in the paper.

Belief revision: from theory to practice

Belief revision is the process of rearranging a knowledge base to preserve global consistency whilst accommodating incoming information. Early approaches to belief revision used symbolic model theoretic methods, considering the problem as one of changi ng a logical theory. More recent approaches have adopted qualitative syntactic methods, taking them into the area of truth maintenance systems, and numerical mathematical methods, thus moving into the mainstream literature of uncertainty management. Multi -agent systems, in which information may come from a variety of human and artificial sources with different degrees of reliability, seem to be a natural domain for belief revision. The aim of this paper is to give a synoptic perspective of this composite subject from the clear air of the high theoretical peaks down to the muddy plain of practical algorithms.

Mental States Recognition from Communication

In order to perform effective communication, agents must be able to foresee the effects of their utterances on the addressee’s mental state. In this paper we study the consequences of an utterance on the mental state of a hearer. Given an agent communication language with a STRIPS-like semantics, we propose a set of criteria that allow the binding of the speaker’s mental state to its uttering of a certain sentence. On the basis of these criteria, we give an abductive procedure that the hearer can adopt to partially r ecognize the speaker’s mental state that led to a specific utterance.

A Fuzzy Semantics for the Resource Description Framework

Semantic Web languages cannot currently represent vague or uncertain information. However, their crisp model-theoretic semantics can be extended to represent uncertainty in much the same way first-order logic was extended to fuzzy logic. We show how the interpretation of an RDF graph (or an RDF Schema ontology) can be a matter of values, addressing a common problem in real-life knowledge management. While unmodified RDF triples can be interpreted according to the new semantics, an extended syntax is needed in order to store fuzzy membership values within the statements. We give conditions an extended interpretation must meet to be a model of an extended graph. Reasoning in the resulting fuzzy languages can be implemented by current inferencers with minimal adaptations.

Revising Beliefs Received from Multiple Sources

During the last decade, the logical framework layed down by Alchourron, Gardenfors and Makinson [1985] deeply influenced the notion of belief revision. Conceiving both, the knowledge space K and incoming information p, as sentences of a propositional language L, they introduced three rational principles for the revision operator (*): AGM1 Consistency: K*p must be consistent AGM2 Minimal Change: K*p should alter as little as possible K AGM3 Priority to the Incoming Information: p must belong to K*p

A Generalized Approach to Consistency Based Belief Revision

This paper presents the basic ideas of a consistency-based approach to Belief Revision that allows the rejection of the newcoming information. This choice is justified for some application domains and leads to the definition of two distinct sets of formulas: the “Belief Base”, which is the eventually inconsistent collection of all the available pieces of information, and the “Reasoning Base” which is the consistent outcome of the revision process. The selection of the Reasoning Base, among the many possible maximally consistent subsets of the Belief Base, is induced by an ordering on the sentences that does not reflect necessarily the chronological order of the arrivals of the information.

A goal-oriented requirements engineering approach for the ambient assisted living domain

The Ambient Assisted Living (AAL) domain is associated with a large number of stakeholders such as patients, their relatives, caregivers and physicians. This variety introduces a great heterogeneity in system requirements, which sometimes results in conflicting needs that must be considered when developing effective AAL systems. In this work we adopt a Goal-Oriented Requirements Engineering (GORE) approach to map out needs and requirements for the AAL domain. Following the requirements mapping, we also propose a preliminary architecture for a home care system (named e-Ward) to assist patients in their domestic environment as if they are in a hospital room.

An augmented reality application for the radio frequency ablation of the liver tumors

Hepatic cancer is one of the most common solid cancers in the world. As surgery of hepatic cancer is seldom applicable, different solutions have been found to cure this disease. One of these is Liver Radiofrequency Ablation. This technique consists in a needle insertion inside the liver parenchyma in order to reach the tumor and in an injection of a radiofrequency current to cause tumor cell necrosis for hyperthermia. The needle placement task is really difficult because surgeon uses ultrasound, CT or MRI two-dimensional image to guide the needle. In this paper we present an Augmented Reality system to help the surgeon to place the needle as best as possible; the application can also help the surgeon during the preoperative planning because it offers various visualization modality of 3D models of the patients organs obtained from the medical images.