Examinando por Autor "Ossowski, Sascha"

Mostrando 1 - 20 de 23

A Proposal for Situation-Aware Evacuation Guidance Based on Semantic Technologies
(Springer, Cham, 2017-06-23) Billhardt, Holger; Dunkel, Juergen; Fernández, Alberto; Lujak, Marin; Hermoso, Ramón; Ossowski, Sascha
Smart Cities require reliable means for managing installations that offer essential services to the citizens. In this paper we focus on the problem of evacuation of smart buildings in case of emergencies. In particular, we present a proposal for an evacuation guidance system that provides individualized evacuation support to people in case of emergencies. The system uses sensor technologies and Complex Event Processing to obtain information about the current situation of a building in each moment. Using semantic Web technologies, this information is merged with static knowledge (special user characteristics, building topology, evacuation knowledge) in order to determine (and dynamically update) the most appropriate individualized evacuation routes for each user.
Agreement Technologies for Coordination in Smart Cities
(MDPI, 2018-05-18) Billhardt, Holger; Fernández, Alberto; Lujak, Marin; Ossowski, Sascha
Many challenges in today’s society can be tackled by distributed open systems. This is particularly true for domains that are commonly perceived under the umbrella of smart cities, such as intelligent transportation, smart energy grids, or participative governance. When designing computer applications for these domains, it is necessary to account for the fact that the elements of such systems, often called software agents, are usually made by different designers and act on behalf of particular stakeholders. Furthermore, it is unknown at design time when such agents will enter or leave the system, and what interests new agents will represent. To instil coordination in such systems is particularly demanding, as usually only part of them can be directly controlled at runtime. Agreement technologies refer to a sandbox of tools and mechanisms for the development of such open multiagent systems, which are based on the notion of agreement. In this paper, we argue that agreement technologies are a suitable means for achieving coordination in smart city domains, and back our claim through examples of several real-world applications.
Automated Legal Reasoning with Discretion to Act using s(LAW)
(Springer, 2023-11-20) Arias, Joaquín; Moreno-Rebato, Mar; Rodríguez-García, José Antonio; Ossowski, Sascha
Automated legal reasoning and its application in smart contracts and automated decisions are increasingly attracting interest. In this context, ethical and legal concerns make it necessary for automated reasoners to justify in human-understandable terms the advice given. Logic Programming, specially Answer Set Programming, has a rich semantics and has been used to very concisely express complex knowledge. However, modelling discretionality to act and other vague concepts such as ambiguity cannot be expressed in top-down execution models based on Prolog, and in bottom-up execution models based on ASP the justifications are incomplete and/or not scalable. We propose to use s(CASP), a top-down execution model for predicate ASP, to model vague concepts following a set of patterns. We have implemented a framework, called s(LAW), to model, reason, and justify the applicable legislation and validate it by translating (and benchmarking) a representative use case, the criteria for the admission of students in the "Comunidad de Madrid"
Bike3S: A tool for bike sharing systems simulation
(Taylor & Francis, 2020-01-30) Fernández, Alberto; Billhardt, Holger; Ossowski, Sascha; Sánchez, Óscar
Vehicle sharing systems are becoming increasingly popular. The effectiveness of such systems depends, among other factors, on different strategic and operational management decisions and policies, like the dimension of the fleet or the distribution of vehicles. It is of foremost importance to be able to anticipate and evaluate the potential effects of such strategies before they can be successfully deployed. In this paper we present Bike3S, a simulator for a station-based bike sharing system. The simulator performs semi-realistic simulations of the operation of a bike sharing system and allows for evaluating and testing different management decisions and strategies. In particular, the simulator has been designed to test different station capacities, station distributions, and balancing strategies. The simulator carries out microscopic agent-based simulations, where users of different types can be defined that act according to their individual goals and objectives which influences the overall dynamics of the whole system.
Decentralizing Coordination in Open Vehicle Fleets for Scalable and Dynamic Task Allocation
(Hindawi, 2020-07-16) Lujak, Marin; Giordani, Stefano; Omicini, Andrea; Ossowski, Sascha
One of the major challenges in the coordination of large, open, collaborative, and commercial vehicle fleets is dynamic task allocation. Self-concerned individually rational vehicle drivers have both local and global objectives, which require coordination using some fair and efficient task allocation method. In this paper, we review the literature on scalable and dynamic task allocation focusing on deterministic and dynamic two-dimensional linear assignment problems. We focus on multiagent system representation of open vehicle fleets where dynamically appearing vehicles are represented by software agents that should be allocated to a set of dynamically appearing tasks. We give a comparison and critical analysis of recent research results focusing on centralized, distributed, and decentralized solution approaches. Moreover, we propose mathematical models for dynamic versions of the following assignment problems well known in combinatorial optimization: the assignment problem, bottleneck assignment problem, fair matching problem, dynamic minimum deviation assignment problem, Σk-assignment problem, the semiassignment problem, the assignment problem with side constraints, and the assignment problem while recognizing agent qualification; all while considering the main aspect of open vehicle fleets: random arrival of tasks and vehicles (agents) that may become available after assisting previous tasks or by participating in the fleet at times based on individual interest.
Dynamic Coordination in Fleet Management Systems: Toward Smart Cyber Fleets
(IEEE Intelligent Systems, 2014) Billhardt, Holger; Fernández, Alberto; Lemus, Lissette; Lujak, Marin; Osman, Nardine; Ossowski, Sascha; Sierra, Carles
Fleet Management Systems are commonly used to coordinate mobility and delivery services in a broad variety of domains. However, their traditional top-down control architecture becomes a bottleneck in open and dynamic environments, where scalability, proactiveness, and autonomy are becoming key factors for their success. In this paper, we first present an abstract event-based architecture for Fleet Management Systems that supports tailoring dynamic control regimes for coordinating fleet vehicles, and illustrate it for the case of medical emergency management. Then, we go one step ahead in the transition towards automatic or driverless fleets, by conceiving Fleet Management Systems in terms of Cyber-Physical Systems, and putting forward the notion of Cyber Fleets. We illustrate the idea in the field of electro mobility, where we expect drivers of smart e-motorbikes (Cyber Vehicles), equipped with an intelligent communication device (Cyber Helmet), to coordinate in a context-aware manner as part of a decentralised Fleet Management System.
Dynamic Coordination of Ambulances for Emergency Medical Assistance Services
(Elsevier, 2014) Billhardt, Holger; Lujak, Marin; Sánchez-Brunete, Vicente; Fernández, Alberto; Ossowski, Sascha
The main objective of emergency medical assistance (EMA) services is to attend patients with sudden dis- eases at any possible location within an area of influence. This usually consists in providing ``in situ¿¿ assistance and, if necessary, the transport of the patient to a medical center. The potential of such systems to reduce mortality is directly related to the travel times of ambulances to emergency patients. An effi- cient coordination of the ambulance fleet of an EMA service is crucial for reducing the average travel times. In this paper we propose mechanisms that dynamically improve the allocation of ambulances to patients as well as the redeployment of available ambulances in the region under consideration. We test these mechanisms in different experiments using historical data from the EMA service of the Auton- omous Region of Madrid in Spain: SUMMA112. The results empirically confirm that our proposal reduces the average response times of EMA services significantly.
Evaluating Collaborative and Autonomous Agents in Data-Stream-Supported Coordination of Mobile Crowdsourcing
(MDPI, 2023-01-05) Bruns, Ralf; Dötterl, Jeremias; Dunkel, Jürgen; Ossowski, Sascha
Mobile crowdsourcing refers to systems where the completion of tasks necessarily requires physical movement of crowdworkers in an on-demand workforce. Evidence suggests that in such systems, tasks often get assigned to crowdworkers who struggle to complete those tasks successfully, resulting in high failure rates and low service quality. A promising solution to ensure higher quality of service is to continuously adapt the assignment and respond to failure-causing events by transferring tasks to better-suited workers who use different routes or vehicles. However, implementing task transfers in mobile crowdsourcing is difficult because workers are autonomous and may reject transfer requests. Moreover, task outcomes are uncertain and need to be predicted. In this paper, we propose different mechanisms to achieve outcome prediction and task coordination in mobile crowdsourcing. First, we analyze different data stream learning approaches for the prediction of task outcomes. Second, based on the suggested prediction model, we propose and evaluate two different approaches for task coordination with different degrees of autonomy: an opportunistic approach for crowdshipping with collaborative, but non-autonomous workers, and a market-based model with autonomous workers for crowdsensing.
Event-Driven Architecture for Decision Support in Traffic Management Systems
(Elsevier, 2011) Dunkel, Jürgen; Fernández, Alberto; Ortiz, Rubén; Ossowski, Sascha
Decision support systems for traffic management systems have to cope with a high volume of events continuously generated by sensors. Conventional software architectures do not explicitly target the efficient processing of continuous event streams. Recently, event-driven architectures (EDA) have been proposed as a new paradigm for event-based applications. In this paper we propose a reference architecture for event-driven traffic management systems, which enables the analysis and processing of complex event streams in real-time and is therefore well-suited for decision support in sensor-based traffic control systems. We will illustrate our approach in the domain of road traffic management. In particular, we will report on the redesign of an intelligent transportation management system (ITMS) prototype for the high-capacity road network in Bilbao, Spain.
Inteligencia Artificial: Ejercicios
(2023) Billhardt, Holger; Fernández Gil, Alberto; Ossowski, Sascha
Inteligencia Artificial: Exámenes
(2023) Billhardt, Holger; Fernández Gil, Alberto; Ossowski, Sascha
Inteligencia Artificial: Guías docentes
(2023) Billhardt, Holger; Fernández Gil, Alberto; Ossowski, Sascha
Inteligencia Artificial: Transparencias
(2023) Billhardt, Holger; Fernández Gil, Alberto; Ossowski, Sascha
Legal and ethical implications of applications based on agreement technologies: the case of auction‐based road intersections
(Springer, 2020) Santos, José‐Antonio; Fernández, Alberto; Moreno‐Rebato, Mar; Billhardt, Holger; Rodríguez‐García, José‐A.; Ossowski, Sascha
Agreement technologies refer to a novel paradigm for the construction of distributed intelligent systems, where autonomous software agents negotiate to reach agreements on behalf of their human users. Smart Cities are a key application domain for agreement technologies. While several proofs of concept and prototypes exist, such systems are still far from ready for being deployed in the real-world. In this paper we focus on a novel method for managing elements of smart road infrastructures of the future, namely the case of auction-based road intersections. We show that, even though the key technological elements for such methods are already available, there are multiple non-technical issues that need to be tackled before they can be applied in practice. For this purpose, we analyse legal and ethical implications of auction-based road intersections in the context of international regulations and from the standpoint of the Spanish legislation. From this exercise, we extract a set of required modifications, of both technical and legal nature, which need to be addressed so as to pave the way for the potential real-world deployment of such systems in a future that may not be too far away.
On admissible behaviours for goal-oriented decision-making of value-aware agents
(Springer, 2023-09) Holgado-Sánchez, Andrés; Arias, Joaquín; Moreno-Rebato, Mar; Ossowski, Sascha
The emerging field of value awareness engineering claims that software agents and systems should be value-aware, i.e. they should be able to explicitly reason about the value-alignment of their actions. Values are often modelled as preferences over states or actions which are then extended to plans. In this paper, we examine the effect of different groundings of values depending on context and claim that they can be used to prune the space of courses of actions that are aligned with them. We put forward several notions of such value-admissible behaviours and illustrate them in the domain of water distribution.
On-Time Delivery in Crowdshipping Systems: An Agent-Based Approach Using Streaming Data
(IOS Press, 2020) Dötterl, Jeremias; Bruns, Ralf; Dunkel, Jürgen; Ossowski, Sascha
In parcel delivery, the "last mile" from the parcel hub to the customer is costly, especially for time-sensitive delivery tasks that have to be completed within hours after arrival. Recently, crowdshipping has attracted increased attention as a new alternative to traditional delivery modes. In crowdshipping, private citizens ("the crowd") perform short detours in their daily lives to contribute to parcel delivery in exchange for small incentives. However, achieving desirable crowd behavior is challenging as the crowd is highly dynamic and consists of autonomous, self-interested individuals. Leveraging crowdshipping for time-sensitive deliveries remains an open challenge. In this paper, we present an agent-based approach to on-time parcel delivery with crowds. Our system performs data stream processing on the couriers' smartphone sensor data to predict delivery delays. Whenever a delay is predicted, the system attempts to forge an agreement for transferring the parcel from the current deliverer to a more promising courier nearby. Our experiments show that through accurate delay predictions and purposeful task transfers many delays can be prevented that would occur without our approach.
Organisational Structures in Next-Generation Distributed Systems: Towards a Technology of Agreement
(IOS Press, 2011) Billhardt, Holger; Centeno, Roberto; Carlos E. Cuesta; Fernández, Alberto; Hermoso, Ramón; Ortiz, Rubén; Ossowski, Sascha; Pérez, José Santiago; Vasirani, Matteo
This article provides a brief overview of the field of coordination in multiagent systems, and outlines its relation to current efforts working towards a paradigm for smart, next-generation distributed systems, where coordination is based on the concept of agreement between computational entities. Two examples are provided to visualize the types of mechanisms that can be part of a ¿technology of agreement¿. They explain how techniques from the field of organisations can be used to further coordination and agreement in open multiagent systems. This approach requires autonomy of the coordinated systems and their constituting agents, implying also the need for eventual reorganization and self-adaptation ¿ hence the article presents also an architectural strategy to tackle the inherent dynamism in these features.
Problem Detection in the Edge of IoT Applications
(UNIR, 2023-07-26) Bernabé-Sánchez, Iván; Fernández, Alberto; Billhardt, Holger; Ossowski, Sascha
Due to technological advances, Internet of Things (IoT) systems are becoming increasingly complex. They are characterized by being multi-device and geographically distributed, which increases the possibility of errors of different types. In such systems, errors can occur anywhere at any time and fault tolerance becomes an essential characteristic to make them robust and reliable. This paper presents a framework to manage and detect errors and malfunctions of the devices that compose an IoT system. The proposed solution approach takes into account both, simple devices such as sensors or actuators, as well as computationally intensive devices which are distributed geographically. It uses knowledge graphs to model the devices, the system's topology, the software deployed on each device and the relationships between the different elements. The proposed framework retrieves information from log messages and processes this information automatically to detect anomalous situations or malfunctions that may affect the IoT system. This work also presents the ECO ontology to organize the IoT system information.
Smart Recommendations for Renting Bikes in Bike-Sharing Systems
(MDPI, 2021-10-16) Billhardt, Holger; Fernández, Alberto; Ossowski, Sascha
Vehicle-sharing systems—such as bike-, car-, or motorcycle-sharing systems—have become increasingly popular in big cities in recent years. On the one hand, they provide a cheaper and environmentally friendlier means of transportation than private cars, and on the other hand, they satisfy the individual mobility demands of citizens better than traditional public transport systems. One of their advantages in this regard is their availability, e.g., the possibility of taking (or leaving) a vehicle almost anywhere in a city. This availability obviously depends on different strategic and operational management decisions and policies, such as the dimension of the fleet or the (re)distribution of vehicles. Agglutination problems—where, due to usage patterns, available vehicles are concentrated in certain areas, whereas no vehicles are available in others—are quite common in such systems, and need to be dealt with. Research has been dedicated to this problem, specifying different techniques to reduce imbalanced situations. In this paper, we present and compare strategies for recommending stations to users who wish to rent or return bikes in station-based bike-sharing systems. Our first contribution is a novel recommendation strategy based on queuing theory that recommends stations based on their utility to the user in terms of lower distance and higher probability of finding a bike or slot. Then, we go one step further, defining a strategy that recommends stations by combining the utility of a particular user with the utility of the global system, measured in terms of the improvement in the distribution of bikes and slots with respect to the expected future demand, with the aim of implicitly avoiding or alleviating balancing problems. We present several experiments to evaluate our proposal with real data from the bike sharing system BiciMAD in Madrid.
Stream-based perception for cognitive agents in mobile ecosystems
(IOS Press, 2019-10-11) Dötterl, Jeremias; Bruns, Ralf; Dunkel, Jürgen; Ossowski, Sascha
Cognitive agent abstractions can help to engineer intelligent systems across mobile devices. On smartphones, the data obtained from onboard sensors can give valuable insights into the user’s current situation. Unfortunately, today’s cognitive agent frameworks cannot cope well with the challenging characteristics of sensor data. Sensor data is located on a low abstraction level and the individual data elements are not meaningful when observed in isolation. In contrast, cognitive agents operate on high-level percepts and lack the means to effectively detect complex spatio-temporal patterns in sequences of multiple percepts. In this paper, we present a stream-based perception approach that enables the agents to perceive meaningful situations in low-level sensor data streams. We present a crowdshipping case study where autonomous, self-interested agents collaborate to deliver parcels to their destinations. We show how situations derived from smartphone sensor data can trigger and guide auctions, which the agents use to reach agreements. Experiments with real smartphone data demonstrate the benefits of stream-based agent perception.