The main goal of the project is the study and development of efficient systems, able to cope with
information from knowledge sources consisting on incomplete information, hence, inconsistent and
vague information. On the one hand, we want to investigate the proper logics to describe such information types, mainly t-norm based logics and fuzzy extensions for description logics. On the other hand, we
will study efficient systems for automatic reasoning, able to infer valid information from the above
mentioned knowledge sources. As the obtained information may be inconsistent, the reasoning
procedures may conclude on wrong information, so, an objective will be to study the application
and development of argumentative models, able to justify the soundness of the obtained conclusions
in front of the final user. In order to bound the response time of the reasoning system we will explore
efficient transformations based on satisfiability and maximum satisfiability problems, that already
have highly efficient solving algorithms. Finally, through the worst-case and typical complexity
study, we will bound the solving hardness for some particular reasoning problems. For typical
case complexity, we will employ either generators of synthetic problems, or real problems obtained
from semantic web ontologies but including uncertainty and vagueness in the information encoded,
according to the studied fuzzy description logics of this project.

Funding: 81.554 €

Self-* systems, where * stands for a number of properties such as self-organisation, self-configuration, self-diagnose or self-repair, are systems capable of managing themselves. They provide the most convenient alternative for software development in open, unstructured and dynamic environments. These are the characteristics of a new surge of emerging application domains composed with a wealth of devices and software and human agents. These applications require the effective coordination among participants to achieve their global and individual goals. Furthermore, coordination mechanisms have to be adapted over time to continue being effective under environmental changes.
Virtual worlds (VW) are interactive, computer generated 3D environments where participants come together for a variety of self and group determined purposes. They are a successful technology to integrate humans in computer systems.
The main aim of this project is to apply multi-agent technologies to the engineering of self-* systems composed of software and/or human agents, while paying special attention to those that are to be virtually embedded. We propose to achieve that aim by fulfilling the following three objectives:

1. To design new computational models and algorithms for their application to the achievement of coordination in self-* systems.

2. To develop a simulation environment to test virtually-embedded self-* systems.

3. To construct three proof-of-concept prototypes that illustrate the algorithms and technologies created in the project.

Case-based reasoning (CBR) combines in an effective manner both learning from experience and usage of domain knowledge. Techniques for case retrieval and reuse should not be studied in an isolated manner; instead they should be designed and evaluated in a framework that integrates different types of CBR systems as proposed in this project.

The goal of this project is to enlarge the capabilities of CBR systems to address three challenges we have identified as significant:

A.    The widespread use of ontologies today raises the issue that domain knowledge expressed in ontological frameworks has to be integrated not only in knowledge-intensive CBR but also indata-intensive CBR,

B.    The realization that all models are partial and each approximates reality differently raises the issue of CBR systems capable of using and integrating experience with multiple sources,

C.      The traditional emphasis on CBR research applied to the problem space raises the issue to focus more research on the solution space for improving the case reuse techniques, retrieval guidance techniques, and analyzing the solution space similarity structure.  

Spanish AC project corresponding to the EUROCORES FP006 project "Logical Models for Reasoning under Vague Information (LoMoReVI)

The main goal is to develop "formal systems combining fuzziness with both uncertainty and truthlikeness". Fuzziness refers to gradual and vague properties, and most successful information based models to reason with vague propositions are those systems of mathematical fuzzy logic called t-norm based fuzzy logics. On the other hand, uncertainty models deal with incomplete information, and from a logical point of view, uncertainty formalisms are captured by intensional, modal-like logics, ... which are non-truth functional. Truthlikeness, probably the less known of the above three notions, can be regarded as a special case of the more general concept of similarity and its logical counterpart as some form of similarity-based reasoning, where the truthlike value of a sentence is considered as its degree of proximity to the truth (even though it may not be true).

We think that defining modal many-valued logical systems is the right way to attack this combination problem, and this will fill an existing gap in the literature. Our efforts will be devoted to semantic issues. In particular we will study the adaptation of the dialogue game semantics for fuzzy logics, which is also a common focus of interest of the other two partners of the full Eurocores project (Prague and Vienna), to some modal expansions of t-norm based fuzzy logics relevant to the above mentioned combinations. Additional issues over the above t-norm based logical systems that we will develop are fuzzy description logics, temporal and dynamic extensions of modal many-valued logics, as well as flexible inconsistency handling mechanisms such as (i) revision/merging operators which have been scarcely considered in the literature in the many-valued context, or (ii) argumentation models in the presence of vagueness/uncertainty.

BROKAPITAL es un proyecto de base tecnológico que busca contribuir a la innovación y mejora de los procesos de interacción y negociación entre emprendedores de base tecnológica e inversores, principalmente de capital riesgo. El propósito es poner a disposición de los agentes que participan en estos procesos todo el poder del actual estado del arte de la ingeniería del conocimiento para minimizar los casos de pérdida de oportunidades por ambas partes.

Electronic institutions (EIs) allow to establish interaction conventions among agents --persons and/or programs--on the basis of a distributed, open and computationally dynamic environment.

This project has as a main goal the study of techniques which allow to provide EIs with autonomic capabilities that allow them to offer a dynamic response under changing circumstances by adopting interaction conventions, producing a high-level development environment for autonomous electronic institutions (AEI).

From all those features characterizing an autonomous system, we will focus mainly on the study of auto configuration and reconfiguration. Besides, the development environment will provide us with tools for specification and analysis of AEI which will allow us to reduce the time and complexity of their development. In order to validate the resulting framework, we will carry out experiments based on real-world problems modelled by means of AEIs.

More information: http://e-institutions.iiia.csic.es

Electronic Institutions are a way to implement interaction conventions for agents -human or software- who can establish commitments on an open environment.
This project involves four lines of activity:
1. Exploration of flexible convention making and enforcement.
2. Study of the usage of institutional constructs in social systems modelling.
3. Development of an institutional software layer to specify, activate and test electronic institutions.
4. Experiments on actual E-Institutions.