Agent based approach to University Timetabling Problem

A concept of agent-based approach to timetabling problem is presented. Based on the problem description and with its formalization the term agent is introduced. Agents act on behalf of entities taking part in the timetabling process (activities, rooms and students) and they interact to maximize their own utility. Also a brief overview of existing approaches is presented

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

Implementación de agentes BDI en JADEX

Este artículo describe, en forma resumida, parte de los trabajos de investigación y desarrollo que se están llevando a cabo en la línea “Agentes y Sistemas Multi-agente” del LIDIC. El objetivo de este trabajo es presentar las principales temáticas que están siendo abordadas actualmente en el área de modelos y arquitecturas de agentes cognitivos, para posibilitar un intercambio de experiencias con otros investigadores participantes delWorkshop, que trabajen en líneas de investigación afines. Uno de los objetivos principales de esta línea, es el estudio y desarrollo de sistemas con agentes basados en el modelo BDI. Las arquitecturas (y modelos) BDI proponen a la trinidad BDI (Beliefs, Desires e Intentions) como los elementos claves del estado mental de un agente para tomar las decisiones acerca de cuándo y cómo actuar. Este tipo de enfoque ha demostrado una gran flexibilidad y efectividad en diversos problemas de gran complejidad del mundo real, lo que ha llevado a un creciente interés en la investigación de sus aspectos téóricos pero tambien de las plataformas que soportan el desarrollo de este tipo de agentes. En este, sentido, el objetivo general de este trabajo es realizar una breve descripción de las motivaciones y objetivos que perseguimos al implementar agentes BDI utilizando frameworks de agentes dedicados a tal fin. En particular, se propone el framework de distribución gratuita Jadex que ya ha sido utilizado en distintos problemas vinculados a la logística de hospitales en Alemania.Eje: Agentes y Sistemas InteligentesRed de Universidades con Carreras en Informática (RedUNCI

Implementación de agentes BDI en JADEX

Este artículo describe, en forma resumida, parte de los trabajos de investigación y desarrollo que se están llevando a cabo en la línea “Agentes y Sistemas Multi-agente” del LIDIC. El objetivo de este trabajo es presentar las principales temáticas que están siendo abordadas actualmente en el área de modelos y arquitecturas de agentes cognitivos, para posibilitar un intercambio de experiencias con otros investigadores participantes delWorkshop, que trabajen en líneas de investigación afines. Uno de los objetivos principales de esta línea, es el estudio y desarrollo de sistemas con agentes basados en el modelo BDI. Las arquitecturas (y modelos) BDI proponen a la trinidad BDI (Beliefs, Desires e Intentions) como los elementos claves del estado mental de un agente para tomar las decisiones acerca de cuándo y cómo actuar. Este tipo de enfoque ha demostrado una gran flexibilidad y efectividad en diversos problemas de gran complejidad del mundo real, lo que ha llevado a un creciente interés en la investigación de sus aspectos téóricos pero tambien de las plataformas que soportan el desarrollo de este tipo de agentes. En este, sentido, el objetivo general de este trabajo es realizar una breve descripción de las motivaciones y objetivos que perseguimos al implementar agentes BDI utilizando frameworks de agentes dedicados a tal fin. En particular, se propone el framework de distribución gratuita Jadex que ya ha sido utilizado en distintos problemas vinculados a la logística de hospitales en Alemania.Eje: Agentes y Sistemas InteligentesRed de Universidades con Carreras en Informática (RedUNCI

Optimization of inpatient hemodialysis scheduling considering efficiency and treatment delays to minimize length of stay

Inpatient dialysis units face an uncertain daily demand of hemodialysis procedures for end-stage renal disease (ESRD) patients hospitalized for health conditions that may or may not be directly related to their renal disease. While hospitalized, these patients must receive hemodialysis in addition to any medical services needed for their primary diagnosis. As a result, when demand for inpatient dialysis is high, treatments and procedures required by these inpatients may be delayed increasing their length of stays (LOS). This research presents an optimization approach for daily scheduling of inpatient hemodialysis to maximize the efficiency of the dialysis unit while minimizing delays of other scheduled procedures that could extend the LOS of the inpatients. The optimization approach takes into account the dialysis protocols prescribed by a treating nephrologist for each dialysis patient, the variable duration of the dialysis treatments, the limited capacity of the dialysis equipment and personnel, as well as the isolation requirements used to mitigate the spread of healthcare-associated infections (HAI). In addition, a variant of the optimization approach is developed that considers uncertainty associated with rescheduling procedures that are delayed and the expected impact on LOS. An experimental performance evaluation illustrates the capability and effectiveness of the proposed scheduling methodologies. The results of this research indicate that the optimization-based scheduling approaches developed in this study could be used on a daily basis by an inpatient dialysis unit to create efficient dialysis schedules

Distributed Multiagent Resource Allocation using Reservations to Improve Handling of Dynamic Task Arrivals

In the artificial intelligence subfield of multi-agent systems, there are many applications for algorithms which optimally allocate a set of resources among many available tasks which demand those resources. In this thesis we present a distributed algorithm to solve this problem which adapts well to dynamic task arrivals, where new work arises at short notice. This algorithm builds on prior work which focused on finding the optimal allocation in a closed environment with a fixed number of tasks. Our algorithm is designed to leverage preemption if it is available, revoking resource allocations to tasks in progress if new opportunities arise which those resources are better suited to handle. However, interrupting tasks in progress is rarely without cost, and our algorithm both respects these costs and may reserve resources to avoid unnecessary costs from hasty allocation. Our multi-agent model assigns a task agent to each task which must be completed and a proxy agent to each resource which is available. These proxy agents are responsible for allocating the resource they manage, while task agents are responsible for learning about their environment and planning out which resources to request for their task. The distributed nature of our model makes it easy to dynamically introduce new tasks with associated task agents. Preemption occurs when a task agent approaches a proxy agent with a sufficiently compelling need that the proxy agent determines the newcomer derives more benefit from the proxy agent's resource than the task agent currently using that resource. We compare to other multi-agent resource allocation frameworks which permit preemption under more conservative assumptions, and show through simulation that our planning and learning techniques allow for improved allocations through more permissive preemption. Our simulations present a medical application which models fallible human resources, though the techniques used are applicable to other domains such as computer scheduling. We then revisit the model with a focus on opportunity cost, introducing resource reservation as an alternative method to preemption for addressing expected future changes in the task allocation environment. Simulations help identify the scenarios where opportunity cost is a significant concern. The model is then further expanded to account for switching costs, where interrupting tasks in progress is worse than simply delaying tasks, and the logical extreme where resource allocation is irrevocable thus encouraging careful decisions about where to commit resources. This thesis makes three primary contributions to multi-agent resource allocation. The first is an improved distributed resource allocation framework which uses Transfer-of-Control strategies and learning to rapidly find good allocations in a dynamic environment. The second is a discussion of the importance of opportunity cost in resource allocation, accompanied by a simple "dummy agent" implementation which validates the use of resource reservation to address scenarios vulnerable to opportunity cost. Finally, the effectiveness of this resource allocation framework with reservation is extended to environments where preemption is costly or impossible

Engineering coordination : eine Methodologie für die Koordination von Planungssystemen

Planning problems, like real-world planning and scheduling problems, are complex tasks. As an efficient strategy for handing such problems is the ‘divide and conquer’ strategy has been identified. Each sub problem is then solved independently. Typically the sub problems are solved in a linear way. This approach enables the generation of sub-optimal plans for a number of real world problems. Today, this approach is widely accepted and has been established e.g. in the organizational structure of companies. But existing interdependencies between the sub problems are not sufficiently regarded, as each problem are solved sequentially and no feedback information is given. The field of coordination has been covered by a number of academic fields, like the distributed artificial intelligence, economics or game theory. An important result is, that there exist no method that leads to optimal results in any given coordination problem. Consequently, a suitable coordination mechanism has to be identified for each single coordination problem. Up to now, there exists no process for the selection of a coordination mechanism, neither in the engineering of distributed systems nor in agent oriented software engineering. Within the scope of this work the ECo process is presented, that address exactly this selection problem. The Eco process contains the following five steps. • Modeling of the coordination problem • Defining the coordination requirements • Selection / Design of the coordination mechanism • Implementation • Evaluation Each of these steps is detailed in the thesis. The modeling has to be done to enable a systemic analysis of the coordination problem. Coordination mechanisms have to respect the given situation and the context in which the coordination has to be done. The requirements imposed by the context of the coordination problem are formalized in the coordination requirements. The selection process is driven by these coordination requirements. Using the requirements as a distinction for the selection of a coordination mechanism is a central aspect of this thesis. Additionally these requirements can be used for documentation of design decisions. Therefore, it is reasonable to annotate the coordination mechanisms with the coordination requirements they fulfill and fail to ease the selection process, for a given situation. For that reason we present a new classification scheme for coordination methods within this thesis that classifies existing coordination methods according to a set of criteria that has been identified as important for the distinction between different coordination methods. The implementation phase of the ECo process is supported by the CoPS process and CoPS framework that has been developed within this thesis, as well. The CoPS process structures the design making that has to be done during the implementation phase. The CoPS framework provides a set of basic features software agents need for realizing the selected coordination method. Within the CoPS process techniques are presented for the design and implementation of conversations between agents that can be applied not only within the context of the coordination of planning systems, but for multiagent systems in general. The ECo-CoPS approach has been successfully validated in two case studies from the logistic domain.Reale Planungsprobleme, wie etwa die Produktionsplanung in einer Supply Chain, sind komplex Planungsprobleme. Eine übliche Strategie derart komplexen Problemen zu lösen, ist es diese Probleme in einfachere Teilprobleme zu zerlegen und diese dann separat, meist sequentiell, zu lösen (divide-and-conquer Strategie). Dieser Ansatz erlaubt die Erstellung von (suboptimalen) Plänen für eine Reihe von realen Anwendungen, und ist heute in den Organisationsstrukturen von größeren Unternehmen institutionalisiert worden. Allerdings werden Abhängigkeiten zwischen den Teilproblemen nicht ausreichend berücksichtigt, da die Partialprobleme sequentiell ohne Feedback gelöst werden. Die erstellten Teillösungen müssen deswegen oft nachträglich koordiniert werden. Das Gebiet der Koordination wird in verschiedenen Forschungsgebieten, wie etwa der verteilten Künstlichen Intelligenz, den Wirtschaftswissenschaften oder der Spieltheorie untersucht. Ein zentrales Ergebnis dieser Forschung ist, dass es keinen für alle Situationen geeigneten Koordinationsmechanismus gibt. Es stellt sich also die Aufgabe aus den zahlreichen vorgeschlagenen Koordinationsmechanismen eine Auswahl zu treffen, die für die aktuelle Situation den geeigneten Mechanismus identifiziert. Für die Auswahl eines solchen Mechanismus existiert bisher jedoch kein strukturiertes Verfahren für die Entwicklung von verteilten Systems und insbesondere im Bereich der Agenten orientierter Softwareentwicklung. Im Rahmen dieser Arbeit wird genau hierfür ein Verfahren vorgestellt, der ECo-Prozess. Mit Hilfe dieses Prozesses wird der Auswahlprozess in die folgenden Schritte eingeteilt: • Modellierung der Problemstellung und des relevante Kontextes • Formulierung von Anforderungen an einen Koordinationsmechanismus (coordination requirements) • Auswahl/Entwurf eines Koordinationsmechanismuses • Implementierung des Koordinationsverfahrens • Evaluation des Koordinationsverfahrens Diese Schritte werden im Rahmen der vorliegenden Arbeit detailliert beschrieben. Die Modellierung der Problemstellung stellt dabei den ersten Schritt dar, um die Problemstellung analytisch zugänglich zu machen. Koordinationsverfahren müssen die Gegebenheiten, den Kontext und die Domäne, in der sie angewendet werden sollen hinreichend berücksichtigen um anwendbar zu sein. Dieses kann über Anforderungen an den Koordinationsprozess formalisiert werden. Der von den Anforderungen getrieben Auswahlprozess ist ein Kernstück der hier vorgestellten Arbeit. Durch die Formulierung der Anforderungen und der Annotation eines Koordinationsmechanismus bezüglich der erfüllten und nicht erfüllten Anforderungen werden die Motive für Designentscheidungen dieses Verfahren expliziert. Wenn Koordinationsverfahren anhand dieser Anforderungen klassifiziert werden können, ist es weiterhin möglich den Auswahlprozess (unabhängig vom ECo-Ansatz) zu vereinfachen und zu beschleunigen. Im Rahmen dieser Arbeit wird eine Klassifikation von Koordinationsansätzen anhand von allgemeinen Kriterien vorgestellt, die die Identifikation von geeigneten Kandidaten erleichtern. Diese Kandidaten können dann detaillierter untersucht werden. Dies wurde in den vorgestellten Fallstudien erfolgreich demonstriert. Für die Unterstützung der Implementierung eines Koordinationsansatzes wird in dieser Arbeit zusätzlich der CoPS Prozess vorgeschlagen. Der CoPS Prozess erlaubt einen ganzheitlichen systematischen Ansatz für den Entwurf und die Implementierung eines Koordinationsverfahrens. Unterstürzt wird der CoPS Prozess durch das CoPS Framework, das die Implementierung erleichtert, indem es als eine Plattform mit Basisfunktionalität eines Agenten bereitstellt, der für die Koordination von Planungssystemen verantwortlich ist. Im Rahmen des CoPS Verfahrens werden Techniken für den Entwurf und die Implementierung von Konversation im Kontext des agenten-orientiertem Software Engineerings ausführlich behandelt. Der Entwurf von Konversationen geht dabei weit über Fragestellung der Formatierung von Nachrichten hinaus, wie dies etwa in den FIPA Standards geregelt ist, und ist für die Implementierung von agentenbasierten Systemen im Allgemeinen von Bedeutung. Die Funktionsweise des ECo-CoPS Ansatzes wird anhand von zweierfolgreich durchgeführten Fallstudien aus dem betriebswirtschaftlichen Kontext vorgestellt