International Journal on Artificial Intelligence Tools

This paper presents a context-aware, multi-agent system called “Confidence” that helps elderly people remain independent longer by detecting falls and unusual movement, which may indicate a health problem. The system combines state-of-the-art sensor technologies and four groups of agents providing a reliable, robust, flexible monitoring system. It can call for help in case of an emergency, and issue warnings if unusual behavior is detected. The first group gathers data from the location and inertial sensors and suppresses noise. The second group reconstructs the position and activity of a person and detects the context. The third group assesses the person's condition in the environment and reacts to critical situations such as falls. The fourth group detects unusual behavior as an indicator of a potential health problem. The system was successfully tested on a scenario consisting of events that were difficult to recognize as falls, as well as in a scenario consisting of normal days and days when the person was ill. It was also demonstrated live several times, with excellent performance in complex situations.

We propose in this paper a novel architecture for human activity monitoring, following conceptual, technical and experimental claims. From a conceptual viewpoint, we propose to approach the interpretation of sensor data as embedded into a multidimensional frame involving functional and non-functional requirements. Functional requirements involve considering the monitored person's specificities as well as the task to be performed. Non-functional requirements qualify the system activity. This frame of interpretation is continuously refined, to cope with evolving situations or expectations from the Observer. From a technical viewpoint, we propose to develop a multi-Agent architecture as a means for dependable, flexible monitoring. This paradigm allows to handle multiple, heterogeneous entities in a unified way. The Agents process incoming data with a dynamic population of hypotheses on several abstraction levels. This reasoning is abductive and fuzzy in nature. From the experimental viewpoint, we propose a dedicated evaluation approach to estimate the interpretative process unfolding. Functional and non-functional properties are presented to discuss the system's effectiveness, informativeness, sensitivity, efficiency and robustness, some of which are supported by qualitative, analytical discussions, others by quantitative measures.

Nowadays Web services are one of the most commonly used technologies for distributed system integration and interoperability. Recently, a new communication technique called WebSockets has appeared for implementing Web services that offer a true server-push mechanism. In this paper we present a system based on it to manage agent communications, and we motivate its use in an Assistive Technologies use case. A new WebSocket Message Transport Protocol is described and an implementation for the Jade platform is presented. Subscription based agent interaction for the use case is presented, along with a comparison between WebSocket and HTTP Message Transport Protocols.

Medical reasoning describes a form of qualitative inquiry that examines the cognitive (thought) processes involved in making medical decision. In this field the goal for diagnostic reasoning is assessing causes of observed conditions in order to make informed choices about treatment. In order to design a diagnostic reasoning method we merge ideas from a hypothetic-deductive method and the Domino model. In this setting, we introduce the so called Hypothetic-Deductive-Domino (HD-D) algorithm. In addition, a multi-agent approach is presented, which takes advantage of the HD-D algorithm for illuminating different standpoints in a diagnostic reasoning and assessment process, and for reaching a well-founded conclusion. This multi-agent approach is based on the so called Observer and Validating agents. The Observer agents are supported by a deductive inference process and the Validating agents are supported by an abductive inference process. The knowledge bases of these agents are captured by a class of possibilistic logic programs. Hence, these agents are able to deal with qualitative information. The approach is illustrated by a real scenario from diagnosing dementia diseases.

In this paper, we propose a simulator for integrated long-term care systems using as a starting point a holistic model of care systems for people that need long term care, the Sustainable Socio-Health Model (SSHM). The implementation of the simulator on the Jason multi-agent platform allows the tool to include the human interactions, preferences, and social abilities that take place between elderly people and the staff of healthcare systems (doctors, social workers and nurses). In addition, the use of this multi-agent platform provides the required scalability for simulating population sizes of different orders of magnitude. The paper shows the model to be implemented in the simulator, the simulator architecture, the types of agents considered, their functionality and the information flow among them. Additionally, it shows the validation of the simulator with real data obtained from empirical studies conducted by the Polibienestar Research Institute in Spain, as well as a performance evaluation that sketches the performance of the simulator when using the centralized Jason infrastructure under different population sizes. Effectively, simulation can provide policy makers with the option of going into a decision theatre and virtually knowing the consequences of different policies prior to determining the real policy to be adopted.

This paper investigates a secure mechanism for Electronic Health Records (EHR) exchange over a Peer to Peer (P2P) agent based coordination framework. Our study is based on the SemHealthCoord framework, a platform for the exchange of EHR between autonomous health organisations that extends the existing interoperability standards as proposed by the Integrating Healthcare Enterprise (IHE). Every health organisation in SemHealthCoord represents a community within a P2P network. Communities use a set of autonomous agents and a set of distributed coordination rules to coordinate the agents in the search of specific health records. To enable secure interactions among communities, we propose the use of asymmetric keys and digital certificates. We specify the interaction protocols to provide integrity and authenticity between the communities, and, to illustrate the scalability of our approach, we evaluate the proposed solution in distributed settings by comparing the performance between secured and unsecured data exchange. The contribution of this work is that enables IHE based health communities to dynamically exchange EHR of patients with a secure P2P agent coordination framework.

A new type of partially global consistency derived from (2, k)-consistency called bounded (2, k)- consistency (B2C-consistency) is presented in this paper. It is designed for application in propositional satisfiability (SAT) as a building block for a preprocessing tool. Together with the new B2C-consistency a special mechanism for selecting regions of the input SAT instance with difficult constraint setup was also proposed. This mechanism is used to select suitable difficult sub-problems whose simplification through consistency can lead to a significant reduction in the effort needed to solve the instance. A new prototype preprocessing tool preprocessSIGMA which is based on the proposed techniques was implemented. As a proof of new concepts a competitive experimental evaluation on a set of relatively difficult SAT instances was conducted. It showed that our prototype preprocessor is competitive with respect to the existent preprocessing tools LiVer, NiVer, HyPre, blocked clause elimination (BCE), and Shatter with saucy 3.0.