iGenda : an event scheduler for common users and centralised systems

The world is walking towards an aged society as a consequence of the increasing rate of longevity in modern cultures. With age comes the fact that memory decreases its efficiency and memory loss starts to surge.Within this context, iGenda is a Personal Memory Assistant (PMA) designed to run on a personal computer or mobile device that tries to help final-users in keeping track of their daily activities. In addition, iGenda has included a Centralised Management System (CMS) on the side of an hospital-like institution, the CMS stands a level above the PMA and the goal is to manage the medical staff (e.g. physicians and nurses) daily work schedule taking into account the patients and resources, communicating directly with the PMA of the patient. This paper presents the platform concept, the overall architecture of the system and the key features on the different agents and components

Intention Reconciliation in the Context of Teamwork: An Initial Empirical Investigation

With growing opportunities for individually motivated agents to work collaboratively to satisfy shared goals, it becomes increasingly important to design agents that can make intelligent decisions in the context of commitments to group activities. In particular, agents need to be able to reconcile their intentions to do team-related actions with other, conflicting intentions. We present the SPIRE experimental system that allows the process of intention reconciliation in team contexts to be simulated and studied. SPIRE enables us to examine the influence of team norms and environmental factors on team members faced with conflicting intentions, as well as the effectiveness of different intention-reconciliation strategies. We discuss results from pilot experiments that confirm the reasonableness of our model of the problem and illustrate some of the issues involved, and we lay the groundwork for future experiments that will allow us to derive principles for designers of collaboration-capable agents.Engineering and Applied Science

Multi-Agent Based Information Systems For Patient Coordination in Hospitals

The health sector is a central domain in every economy. It is challenged by progressing costs and funding issues. Hospitals play a major role for the examination and treatment of patients. The sequence how patients are assigned to hospital units determines the quality of treatment, the resource utilization, as well as the patients’ overall treatment time. Thus, efficient scheduling of patients in hospitals is crucial. Current approaches disregard the decentral organization in hospitals and neglect the varying pathway of patients since they often focus on one single unit solely. We propose an agent-based coordination mechanism that overcomes these limitations. Patients and hospital resources are modeled as autonomous software agents which follow their own objectives. This reflects the decentralized structure in hospitals. Agents are coordinated by a distributed mechanism where software agents improve their situation through negotiations which moves towards an overall pareto-optimum. We show promising evaluations based on experiments

An Agent-Based Decision Support System for Hospitals Emergency Departments

AbstractModeling and simulation have been shown to be useful tools in many areas of the Healthcare operational management, field in which there is probably no area more dynamic and complex than hospital emergency departments (ED). This paper presents the results of an ongoing project that is being carried out by the Research Group in Individual Oriented Modeling (IoM) of the University Autonoma of Barcelona (UAB) with the participation of Hospital of Sabadell ED Staff Team. Its general objective is creating a simulator that, used as decision support system (DSS), aids the heads of the ED to make the best informed decisions possible. The defined ED model is a pure Agent-Based Model, formed entirely of the rules governing the behavior of the individual agents which populate the system. Two distinct types of agents have been identified, active and passive. Active agents represent human actors, meanwhile passive agents represent services and other reactive systems. The actions of agents and the communication between them will be represented using Moore state machines extended to include probabilistic transitions. The model also includes the environment in which agents move and interact. With the aim of verifying the proposed model an initial simulation has been created using NetLogo, an agent-based simulation environment well suited for modeling complex systems

An intelligent multi-agent memory assistant

World population is ageing and increasingly scarce resources are required to cover the needs of everyone adequately. Medical conditions, especially memory problems, restrict the daily life of a broad slice of the elderly population, affect their independence. To prevent this, providing the right care and assistance while having in mind the costs implicated is essential. One possible path is to work with resources that we already have today and create innovative solutions to achieve the required level of support. There are not many solution either technological or not to prevent memory loss. In this work we present a possible solution aimed at restoring or maintaining the independence of elderly people, through the use of so-called Memory Assistants. We thus present an Intelligent Multi-Agent Memory Assistant designed to help people with memory problems remember their events and activities. The implementation of an event manager, free time manger, medication remainder and a sensory system, to manage and monitor the user, we aim to improve their quality of life and increase their independence

Agent based simulation to optimise emergency departments

Nowadays, many of the health care systems are large and complex environments and quite dynamic, specifically Emergency Departments, EDs. It is opened and working 24 hours per day throughout the year with limited resources, whereas it is overcrowded. Thus, is mandatory to simulate EDs to improve qualitatively and quantitatively their performance. This improvement can be achieved modelling and simulating EDs using Agent-Based Model, ABM and optimising many different staff scenarios. This work optimises the staff configuration of an ED. In order to do optimisation, objective functions to minimise or maximise have to be set. One of those objective functions is to find the best or optimum staff configuration that minimise patient waiting time. The staff configuration comprises: doctors, triage nurses, and admissions, the amount and sort of them. Staff configuration is a combinatorial problem, that can take a lot of time to be solved. HPC is used to run the experiments, and encouraging results were obtained. However, even with the basic ED used in this work the search space is very large, thus, when the problem size increases, it is going to need more resources of processing in order to obtain results in an acceptable time

The Influence of Social Norms and Social Consciousness on Intention Reconciliation

Research on resource-bounded agents has established that rational agents need to be able to revise their commitments in light of new opportunities. In the context of collaborative activities, rational agents must be able to reconcile their intentions to do team-related actions with other, conflicting intentions. The SPIRE experimental system allows the process of intention reconciliation in team contexts to be simulated and studied. Initial work with SPIRE examined the impact of environmental factors and agent utility functions on individual and group outcomes in the context of one set of social norms governing collaboration. This paper extends those results by further studying the effect of environmental factors and the agents' level of social consciousness and by comparing the impact of two different types of social norms on agent behavior and outcomes. The results show that the choice of social norms influences the accuracy of the agents' responses to varying environmental factors, as well as the effectiveness of social consciousness and other aspects of agents' utility functions. In experiments using heterogeneous groups of agents, both sets of norms were susceptible to the free-rider effect. However, the gains of the less responsible agents were minimal, suggesting that agent designers would have little incentive to design agents that deviate from the standard level of responsibility to the group.Engineering and Applied Science