46 research outputs found
Uncertainty of the implementation time of geodynamic monitoring system in multi-criteria ranking of alternatives
The paper deals with the problem of ranking alternatives to geodynamic monitoring systems in the case of uncertainty of their implementation time. The problem is characterized by the fact that the choice of alternatives and the effect of it depends on the quality properties of the applied organizational and technical solutions, taking into account the time of implementation. The ordering of alternatives is proposed taking into account the uncertainty of the implementation time factors. Ranking is realized by comparing the trees of functional characteristics of alternatives taking into account the compliance of their characteristics with time-varying requirement
On the Combination of Game-Theoretic Learning and Multi Model Adaptive Filters
This paper casts coordination of a team of robots within the framework of game theoretic learning algorithms. In particular a novel variant of fictitious play is proposed, by considering multi-model adaptive filters as a method to estimate other players’ strategies. The proposed algorithm can be used as a coordination mechanism between players when they should take decisions under uncertainty. Each player chooses an action after taking into account the actions of the other players and also the uncertainty. Uncertainty can occur either in terms of noisy observations or various types of other players. In addition, in contrast to other game-theoretic and heuristic algorithms for distributed optimisation, it is not necessary to find the optimal parameters a priori. Various parameter values can be used initially as inputs to different models. Therefore, the resulting decisions will be aggregate results of all the parameter values. Simulations are used to test the performance of the proposed methodology against other game-theoretic learning algorithms.</p
A Call for Standardization and Validation of Text Style Transfer Evaluation
Text Style Transfer (TST) evaluation is, in practice, inconsistent.
Therefore, we conduct a meta-analysis on human and automated TST evaluation and
experimentation that thoroughly examines existing literature in the field. The
meta-analysis reveals a substantial standardization gap in human and automated
evaluation. In addition, we also find a validation gap: only few automated
metrics have been validated using human experiments. To this end, we thoroughly
scrutinize both the standardization and validation gap and reveal the resulting
pitfalls. This work also paves the way to close the standardization and
validation gap in TST evaluation by calling out requirements to be met by
future research.Comment: Accepted to Findings of ACL 202
A System for Deduction-based Formal Verification of Workflow-oriented Software Models
The work concerns formal verification of workflow-oriented software models
using deductive approach. The formal correctness of a model's behaviour is
considered. Manually building logical specifications, which are considered as a
set of temporal logic formulas, seems to be the significant obstacle for an
inexperienced user when applying the deductive approach. A system, and its
architecture, for the deduction-based verification of workflow-oriented models
is proposed. The process of inference is based on the semantic tableaux method
which has some advantages when compared to traditional deduction strategies.
The algorithm for an automatic generation of logical specifications is
proposed. The generation procedure is based on the predefined workflow patterns
for BPMN, which is a standard and dominant notation for the modeling of
business processes. The main idea for the approach is to consider patterns,
defined in terms of temporal logic,as a kind of (logical) primitives which
enable the transformation of models to temporal logic formulas constituting a
logical specification. Automation of the generation process is crucial for
bridging the gap between intuitiveness of the deductive reasoning and the
difficulty of its practical application in the case when logical specifications
are built manually. This approach has gone some way towards supporting,
hopefully enhancing our understanding of, the deduction-based formal
verification of workflow-oriented models.Comment: International Journal of Applied Mathematics and Computer Scienc
Classification of Explainable Artificial Intelligence Methods through Their Output Formats
Machine and deep learning have proven their utility to generate data-driven models with high accuracy and precision. However, their non-linear, complex structures are often difficult to interpret. Consequently, many scholars have developed a plethora of methods to explain their functioning and the logic of their inferences. This systematic review aimed to organise these methods into a hierarchical classification system that builds upon and extends existing taxonomies by adding a significant dimension—the output formats. The reviewed scientific papers were retrieved by conducting an initial search on Google Scholar with the keywords “explainable artificial intelligence”; “explainable machine learning”; and “interpretable machine learning”. A subsequent iterative search was carried out by checking the bibliography of these articles. The addition of the dimension of the explanation format makes the proposed classification system a practical tool for scholars, supporting them to select the most suitable type of explanation format for the problem at hand. Given the wide variety of challenges faced by researchers, the existing XAI methods provide several solutions to meet the requirements that differ considerably between the users, problems and application fields of artificial intelligence (AI). The task of identifying the most appropriate explanation can be daunting, thus the need for a classification system that helps with the selection of methods. This work concludes by critically identifying the limitations of the formats of explanations and by providing recommendations and possible future research directions on how to build a more generally applicable XAI method. Future work should be flexible enough to meet the many requirements posed by the widespread use of AI in several fields, and the new regulation
TRAMMAS: Enhancing Communication in Multiagent Systems
Tesis por compendio[EN] Over the last years, multiagent systems have been proven to be a powerful and versatile paradigm, with a big
potential when it comes to solving complex problems in dynamic and distributed environments, due to their flexible
and adaptive behavior. This potential does not only come from the individual features of agents (such as autonomy,
reactivity or reasoning power), but also to their capability to communicate, cooperate and coordinate in order to
fulfill their goals. In fact, it is this social behavior what makes multiagent systems so powerful, much more than the
individual capabilities of agents.
The social behavior of multiagent systems is usually developed by means of high
level abstractions, protocols and languages, which normally rely on (or at least, benefit from) agents being able to
communicate and interact indirectly. However, in the development process, such high level concepts habitually
become weakly supported, with mechanisms such as traditional messaging, massive broadcasting, blackboard
systems or ad hoc solutions. This lack of an appropriate way to support indirect communication in actual multiagent
systems compromises their potential.
This PhD thesis proposes the use of event tracing as a flexible, effective and efficient support for indirect interaction
and communication in multiagent systems. The main contribution of this thesis is TRAMMAS, a generic, abstract
model for event tracing support in multiagent systems. The model allows all entities in the system to share their
information as trace events, so that any other entity which require this information is able to receive it. Along with
the model, the thesis also presents an abstract architecture, which redefines the model in terms of a set of tracing
facilities that can be then easily incorporated to an actual multiagent platform. This architecture follows a
service-oriented approach, so that the tracing facilities are provided in the same way than other traditional services
offered by the platform. In this way, event tracing can be considered as an additional information provider for
entities in the multiagent system, and as such, it can be integrated from the earliest stages of the development
process.[ES] A lo largo de los últimos años, los sistemas multiagente han demostrado ser un paradigma potente y versátil,
con un gran potencial a la hora de resolver problemas complejos en entornos dinámicos y distribuidos, gracias a
su comportamiento flexible y adaptativo. Este potencial no es debido únicamente a las características individuales
de los agentes (como son su autonomía, y su capacidades de reacción y de razonamiento), sino que también se
debe a su capacidad de comunicación y cooperación a la hora de conseguir sus objetivos. De hecho, por encima
de la capacidad individual de los agentes, es este comportamiento social el que dota de potencial a los sistemas
multiagente.
El comportamiento social de los sistemas multiagente suele desarrollarse empleando abstracciones, protocolos y
lenguajes de alto nivel, los cuales, a su vez, se basan normalmente en la capacidad para comunicarse e
interactuar de manera indirecta de los agentes (o como mínimo, se benefician en gran medida de dicha
capacidad). Sin embargo, en el proceso de desarrollo software, estos conceptos de alto nivel son soportados
habitualmente de manera débil, mediante mecanismos como la mensajería tradicional, la difusión masiva, o el uso
de pizarras, o mediante soluciones totalmente ad hoc. Esta carencia de un soporte genérico y apropiado para la
comunicación indirecta en los sistemas multiagente reales compromete su potencial.
Esta tesis doctoral propone el uso del trazado de eventos como un soporte flexible, efectivo y eficiente para la
comunicación indirecta en sistemas multiagente. La principal contribución de esta tesis es TRAMMAS, un modelo
genérico y abstracto para dar soporte al trazado de eventos en sistemas multiagente. El modelo permite a
cualquier entidad del sistema compartir su información en forma de eventos de traza, de tal manera que cualquier
otra entidad que requiera esta información sea capaz de recibirla. Junto con el modelo, la tesis también presenta
una arquitectura {abs}{trac}{ta}, que redefine el modelo como un conjunto de funcionalidades que pueden ser
fácilmente incorporadas a una plataforma multiagente real. Esta arquitectura sigue un enfoque orientado a
servicios, de modo que las funcionalidades de traza son ofrecidas por parte de la plataforma de manera similar a
los servicios tradicionales. De esta forma, el trazado de eventos puede ser considerado como una fuente adicional
de información para las entidades del sistema multiagente y, como tal, puede integrarse en el proceso de
desarrollo software desde sus primeras etapas.[CA] Al llarg dels últims anys, els sistemes multiagent han demostrat ser un paradigma potent i versàtil, amb un gran
potencial a l'hora de resoldre problemes complexes a entorns dinàmics i distribuïts, gràcies al seu comportament
flexible i adaptatiu. Aquest potencial no és només degut a les característiques individuals dels agents (com són la
seua autonomia, i les capacitats de reacció i raonament), sinó també a la seua capacitat de comunicació i
cooperació a l'hora d'aconseguir els seus objectius. De fet, per damunt de la capacitat individual dels agents, es
aquest comportament social el que dóna potencial als sistemes multiagent.
El comportament social dels sistemes multiagent solen desenvolupar-se utilitzant abstraccions, protocols i
llenguatges d'alt nivell, els quals, al seu torn, es basen normalment a la capacitat dels agents de comunicar-se i
interactuar de manera indirecta (o com a mínim, es beneficien en gran mesura d'aquesta capacitat). Tanmateix, al
procés de desenvolupament software, aquests conceptes d'alt nivell son suportats habitualment d'una manera
dèbil, mitjançant mecanismes com la missatgeria tradicional, la difusió massiva o l'ús de pissarres, o mitjançant
solucions totalment ad hoc. Aquesta carència d'un suport genèric i apropiat per a la comunicació indirecta als
sistemes multiagent reals compromet el seu potencial.
Aquesta tesi doctoral proposa l'ús del traçat d'esdeveniments com un suport flexible, efectiu i eficient per a la
comunicació indirecta a sistemes multiagent. La principal contribució d'aquesta tesi és TRAMMAS, un model
genèric i abstracte per a donar suport al traçat d'esdeveniments a sistemes multiagent. El model permet a
qualsevol entitat del sistema compartir la seua informació amb la forma d'esdeveniments de traça, de tal forma que
qualsevol altra entitat que necessite aquesta informació siga capaç de rebre-la. Junt amb el model, la tesi també
presenta una arquitectura abstracta, que redefineix el model com un conjunt de funcionalitats que poden ser
fàcilment incorporades a una plataforma multiagent real. Aquesta arquitectura segueix un enfoc orientat a serveis,
de manera que les funcionalitats de traça són oferides per part de la plataforma de manera similar als serveis
tradicionals. D'aquesta manera, el traçat d'esdeveniments pot ser considerat com una font addicional d'informació
per a les entitats del sistema multiagent, i com a tal, pot integrar-se al procés de desenvolupament software des de
les seues primeres etapes.Búrdalo Rapa, LA. (2016). TRAMMAS: Enhancing Communication in Multiagent Systems [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/61765TESISCompendi
A Review of Approaches for Sensing, Understanding, and Improving Occupancy-Related Energy-Use Behaviors in Commercial Buildings
Buildings currently account for 30–40 percent of total global energy consumption. In particular, commercial buildings are responsible for about 12 percent of global energy use and 21 percent of the United States’ energy use, and the energy demand of this sector continues to grow faster than other sectors. This increasing rate therefore raises a critical concern about improving the energy performance of commercial buildings. Recently, researchers have investigated ways in which understanding and improving occupants’ energy-consuming behaviors could function as a cost-effective approach to decreasing commercial buildings’ energy demands. The objective of this paper is to present a detailed, up-to-date review of various algorithms, models, and techniques employed in the pursuit of understanding and improving occupants’ energy-use behaviors in commercial buildings. Previous related studies are introduced and three main approaches are identified: (1) monitoring occupant-specific energy consumption; (2) Simulating occupant energy consumption behavior; and (3) improving occupant energy consumption behavior. The first approach employs intrusive and non-intrusive load-monitoring techniques to estimate the energy use of individual occupants. The second approach models diverse characteristics related to occupants’ energy-consuming behaviors in order to assess and predict such characteristics’ impacts on the energy performance of commercial buildings; this approach mostly utilizes agent-based modeling techniques to simulate actions and interactions between occupants and their built environment. The third approach employs occupancy-focused interventions to change occupants’ energy-use characteristics. Based on the detailed review of each approach, critical issues and current gaps in knowledge in the existing literature are discussed, and directions for future research opportunities in this field are provided