Nowadays, AI techniques are pervading all sectors of economy and society for supporting decision making, for identification of customer segments, for diagnosis generation, for finding relationships between causes and consequences, for preventing undesired situations (e.g. breakdowns, illnesses, etc.), for managing digital devices such as smart sensors, mechanical arms or artificial eyes, and so on. The transversality of AI and its ability to emulate intelligence in the resolution of challenging problems has currently placed AI at the focus of problem solving in all areas in our society.
This book aims at providing a current image of what is being achieved and what is under development at the moment in AI. As such, its contents are representative of the diversity of approaches and applications which are currently being researched. But it also presents invited contributions which deal with some of the challenges that must be explored in the next decade. Specifically, the research works included in this book can be categorized into the following areas: logic, satisfiability and fuzzy sets; classifiers, networks and machine learning; data science, recommender systems, case-based reasoning; natural language and sound processing; cognitive systems and agents; and computer vision and robotics. It also presents current AI challenges and new trends like big data, spatial problem solving, ethics and AI, and how blockchain impacts AI.
The section on Logic, satisfiability and fuzzy sets presents works on: clause branching for improving MaxSAT and MinSAT solvers; using decimation to improve solvers in large distributed constraint optimization problems; applying horn clauses for classifying and generating explanations; and defining a lattice structure for the set of interval-valued fuzzy qualitative labels.
The section Classifiers, networks and machine learning includes applications on: predicting people's next location; finding the optimal sensor placement in big-size water distribution systems; forecasting wind time series; sorting hams; classifying visitors in a tourist attraction; quantifying similarities between medical drugs; developing a universal encoder for time series; determining modern versus classic style in fashion; capturing equivariant features (related to illumination and rotation) in a new feature representation for deep learning; emulating brain prediction as a set of neural networks that perform Bayesian inference; and detecting shock fronts in computational fluid mechanics to find structures in computational astrophysics plasma simulations.
The following section on Data science, recommender systems, and case-based reasoning presents advances on: obesity prediction; including the context in playlist music recommendations; discovering the most probable sequences of web domains visited by people as input to marketing campaign design; supporting responsible repetitive research and innovation in health science using a case-based reasoning tool; developing personal menu planners depending on people's allergies, intolerances, preferences or diets; integrating semantic criteria into a recommender system; labeling feature-trees for case-base maintenance; and on analysing the utility and risk of masked data applied in big data algorithms.
Next section on Natural language and sound processing gathers studies on: visualizing and analysing sentiments in tweets using manifold dimensionality reduction; detecting irony in Twitter using convolutional neural networks; finding out if Twitter messages impact in stock liquidity; analysing agreements in Reddit-database comments using an argumentation approach; enhancing speech using multivariate empirical mode decomposition; classifying and generalizing parameter combinations in sound design; computing a distance for WordNet concepts based on visual features learnt from ImageNet; and on detecting and recognizing text in images using a language model and visual context information.
The section Cognitive systems and agents joins works which research on: using wearable sensors to detect workload on driving simulated scenarios; introducing the notion of trust in the form of mutual agreements between agents that might enhance stability in the formation of conventions such as turn-taking; developing a framework for organizations to become cognitive systems using a knowledge management process; determining the factors that can accelerate the emergence of collaborative behaviours among independent selfish learning agents (i.e. loss aversion); developing and evaluating an architecture for sentient embodied conversational agents with proactive and sensitive behaviours in educational applications; and on how intelligence can be defined as a generic statistical mechanics theory.
The section on Computer vision and robotics presents research works on: segmenting brain magnetic resonance images using multiphase active contours; estimating vehicle 3D pose from single monocular RGB images using a new architecture, G-Net, based on convolutional neural networks; classifying food attributes (cuisine origin and flavor) using a multi-scale convolutional network; improving retinal image segmentation based on conditional generative adversarial networks to obtain the optic disc; detecting foreground in multi-target fish tracking videos using fully connected convolutional neural networks; improving breast density segmentation using conditional generative adversarial networks; adapting robotic manipulation for industrial environments where teams are built by humans and robots; dealing with the anchoring problem (relating sensed data to symbolic information) in robotic container/bin picking challenges; and analysing human walking and gait behaviour from the interaction between the i-Walker automated rollator and its users.
The invited contribution by Ricardo Baeza-Yates (CTO of NTENT, California, USA, and UPF, Catalonia) on big data technologies outlines that the challenges to face by the companies are many (transparency, explainability, ethics, privacy, etc.) and questions the real need to indiscriminately deal with bigdata, proposing a more critical approach where identifying the right data to analyze is more relevant that the datasize itself. The invited contribution by Carlos Mérida (Accenture-Financial Services, Barcelona, Catalonia, Spain) on blockchain presents this emerging technology as a multi-agent system for data and process managing in a decentralised and secured manner, while analysing its opportunities in AI. The invited contribution by Christian Freksa (University of Bremen, Bremen Spatial Cognition Centre, Germany) on spatial problem solving explains that spatial problems (i.e. untangling cables, finding routes, solving puzzles, etc.) can be solved by cognitive agents either: (i) directly in space by means of perception and manipulation or (ii) they can be transformed into abstract representations to be solved by computational reasoning and then being transformed back into physical space; and it proposes “mild abstraction” as a way of combining best features of both solving methods. And the invited contribution by Luc Steels (ICREA/Institut de Biologia Evolutiva, UPF-CSIC, Catalonia) on the ethical use of AI provides ideas to foster positive uses of AI (i.e. improve healthcare, aid environmental monitoring, support community formation, make culture more widely accessible, etc.) and guard us against negative ones (i.e. perpetuation of racial and gender bias in recruitment, manipulation of public opinion, enforcing senseless bureaucracy, cyberattacks, autonomous weapons, etc.) building further on the “Barcelona Declaration for the Proper Development and Use of AI in Europe”.
Barcelona Declaration: http://www.iiia.csic.es/barcelonadeclaration/
Barcelona Declaration: http://www.iiia.csic.es/barcelonadeclaration/
This book is the outcome of the 21st edition of the International Conference of the Catalan Association for Artificial Intelligence (CCIA 2018
This year, the Catalan Association for Artificial Intelligence (ACIA
ACIA: https://www.acia.cat/ EurAI: https://www.eurai.org/
The chairs of 21st edition of CCIA would like to express our sincere gratitude to the authors for their contributions to this book, to the invited authors for their enlightening contributions, and to all members of the Program and Organizing Committees who have worked hard to make CCIA'18 a success. We also thank the support of a non-neglectable number of scientific program members and authors who were formed in the Catalan AI community and are now developing their scientific activities in international research centers all over the world: Germany, Italy, Venezuela, Brazil, UK, Australia, France, Switzerland, Czech Republic, Sweden and Andorra. Last but not least, we would like to thank Josep Pujol and Aïda Valls, ACIA president and vicepresident, respectively, and all ACIA main board members for their kind support organizing this CCIA'18 were we will also commemorate the 25th anniversary of ACIA.
We wish all participants a successful and inspiring conference and a pleasant stay in Roses.
Zoe Falomir, University of Bremen, Germany (U. Bremen)
Karina Gibert, Universitat Politècnica de Catalunya – BarcelonaTech (UPC)
Enric Plaza, IIIA-CSIC