Acquired Brain Injury (ABI) constitutes a major and increasing social and healthcare concern of high diagnostic and therapeutic complexity. Its incidence and survival rate after the initial critical phases makes it a prevalent problem that needs to be addressed. ABI patients frequently suffer from a series of cognitive disorders related to memory, attention, language, or executive functions. Cognitive rehabilitation aims to reduce the impact of the disabling conditions in order to reduce functional limitations and increase patient's autonomy. For the rehabilitation process to be more effective, treatments must be intensive, personalized to the patient's condition and evidence-based; and require constant monitoring. The main goal of the IIIA team is the research on new machine learning/CBR techniques able to propose and revise personalized therapies in real-time.

Digital games that are worth playing by older people are a new type of digital games that can reinforce and exploit the strengths of older people as individuals and game players rather than merely compensating for their limitations, reduce isolation and foster socialisation, both offline and online, and improve the physical and psychosocial wellbeing of older people. The research conducted in the WorthPlay project aims to enable an understanding and development of these types of digital games, and is grounded in ethnography, participatory and iterative design, and experiences of digital game play. This research will be conducted within the context of designing, developing and evaluating a prototype of an online game that is worth playing by older people, by involving and engaging in the research a user group consisting of older people of mixed gender and expertise playing games, and relevant members of their social circles. WorthPlay will take the state of the art of human-computer interaction research with older people and digital games forward by producing a human taxonomy of digital games for older people; providing a deeper understanding of everyday digital game by older people, of the challenges and opportunities of emerging human-game interaction styles and gaming platforms to improve the accessibility and playability of digital games for older people, and their physical and psychosocial wellbeing, of game adaptation to individual users, and of cultural similarities and differences in digital game play. WorthPlay will also improve relevant methodological aspects of human-computer interaction research with older people by looking into ethnography, user engagement, and iterative and participatory design, in out-of-laboratory conditions over extended periods of time. WorthPlay will also develop a pipeline to integrate the technology and research created during the project into marketable outcomes, and develop original methods of marketing digital games to the older population.

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BUSCAMEDIA aims at significant advances in the areas of semantic search, audiovisual production and riche media distribution thgough the creation of a unique semantic multimedia search engine. Specifically, the involvement of IIIA-CSIC is on the automatic generation of narrative content, such as summaries of soccer matches, or news shows. More information can be found at the overall BUSCAMEDIA page: http://www.cenitbuscamedia.es/

The PON project studies container loading when objects are nonorthogonal, but their shape is represented in terms of polyhedra.

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.  

Case-based reasoning (CBR) combines in an effective manner both learning from examples 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 model in a framework that integrates different types of CBR systems as proposed in this project.
The main objectives of the project can be summarized as follows:

• new ways to use techniques of soft computing for CBR,
• techniques for case reuse of a declarative and generic nature,
• techniques for case retrieval in knowledge-intensive CBR systems,
• integrating ontologies both in CBR systems and retrieval and reuse techniques
• maintenance techniques both for case bases and for CBR systems capable of dealing with issues arising from design, implementation, and deployment of industrial strength CBR systems,
• the empirical evaluation of the developed techniques by means of CBR prototypes implemented for several experimental domains, and
• developing component-based software platforms to support CBR systems development.

Currently, society begins to see some new hardware devices, such as the Personal Digital Assistants (PDAs), mobile phones with increasing computing capabilities, or, even, new programmable freezers or washing machines with network connections. In this type of computation, the context that surrounds people has the ability of recognising us, exchanging information with us, and adapting to our needs. From a scientific point of view, this new computing paradigm poses numerous and very important questions for the eventual development of commercial applications of this technology. There are already some mature technologies that, from a standalone point of view, have shown to be successful in related domains, such as Internet, in relation to their ability to connect people with each other and with the distributed information.

Examples of these technologies within the field of Artificial Intelligence are multi-agent systems, planning (and scheduling), machine learning, or user modelling. However, the future generation of viable commercial applications of interest to people requires the analysis how these techniques can be integrated within a single tool or system, so that it would be possible to develop industrial applications of ubiquitous computing. Up to now, very few researchers in the world have focused on this type of research, basically due to the need of expertise within the same group in a very diverse and disperse set of techniques.

The main objective of the project is the analysis, design and implementation of a multi-agent system with the ability to perform hierarchical, temporal and resource planning and scheduling in the area of ubiquitous computing. The system will also be dynamic in that it will be able to learn from past problem solving experiences, as well as automatically acquiring a user model. To show the viability of the approach in a specific domain, we will focus on an application of e-tourism within a given city.

The aim of the project is to work on different aspects of content-based music processing. The project will study and develop tools for musical content extraction, modeling, and processing. Specifically, we will investigate the use of artificial intelligence techniques, such as case-based reasoning, for content-based melody processing.