15^th Mexican International Conference on Artificial Intelligence

Title: Towards the Use of Authorship Attribution as Forensic Evidence

Abstract: Authorship attribution is the attempt to reveal the authors behind texts based on the assumption that the personal style of authors can be quantified and represented within a computational model. This line of research has a long history and it used to be mainly associated with analysis of literary texts of disputed authorship. Given the vast amount of texts in electronic form in countless media, authorship analysis can now play a crucial role in the framework of forensic applications as well as in social media analytics. Despite the fact that significant progress is reported in relevant literature, it is still questionable whether this technology is reliable enough to be used as evidence in court. This talk will focus on the main factors that are associated with using authorship attribution as forensic evidence. Moreover it will present recent advances in this field that aim at this direction.

Title: Cloud Robotics

Abstract: Cloud Robotics is an emerging field within robotics, currently covering various application domains and robot network paradigms. Cloud Robotics was born from the merger of cloud technologies and robotics. Cloud technology-based computing—or simply Cloud Computing—is one of the most dynamically growing areas of Info-Communication Technologies (ICT). The presentation summarizes the basics of cloud computing, namely the main idea, the definition, the cloud model composed of essential characteristics, service models and deployment models. The next part provides a structured, systematic overview of the numerous definitions, concepts and technologies linked to Cloud Robotics and cloud technologies in a broader sense. It also presents a roadmap for the near future, describing development trends and emerging application areas. Cloud Robotics may have a significant role in the future as an explicitly human-centered technology, capable of addressing the dire needs of our society. Finally some cloud robotics projects are discussed. The last part of the presentation summarizes the results and ideas of a new generation internet and Cloud Technology based Virtual Collaboration Arena (VirCA) developed in Hungary and some of its application possibilities in Cloud Robotics. VirCA provides a platform where users can build, share and manipulate 3D content, and collaboratively interact with real-time processes in a 3D context, while the participating hardware and software devices can be spatially and/or logically distributed and connected together via IP network. The 3D content and processes in VirCA can be synchronized with the real world, which allows the combination of reality and virtual world in the collaboration arena.

Title: Decision Making under Interval (and More General) Uncertainty: Monetary vs. Utility Approaches

Abstract: How to make a decision under interval uncertainty? In many situations, e.g., in financial and economic decision making, the decision results either in a money gain (or loss) and/or in the gain of goods that can be exchanged for money or for other goods. In such situations, interval uncertainty means that we do not know the exact amount of money that we will get for each possible decision, we only know lower and upper bounds on this amount. In this case, a natural idea is to assign a fair price to different alternatives, and then to use these fair prices to select the best alternative. In the talk, we show how to assign a fair price under interval uncertainty. We also explain how to assign a fair price in the case of more general types of uncertainty such as p-boxes (bounds on cumulative distribution function), twin intervals (when we only know approximate bounds), fuzzy values (when we have imprecise expert estimates of the gains), etc. In other situations, e.g., when buying a house to live in or selecting a movie to watch, the result of the decision is the decision maker's own satisfaction. In such situations, a more adequate approach is to use utilities - a quantitative way of describing user's preferences. In this talk, after a brief introduction describing what are utilities, how to evaluate them, and how to make decisions based on utilities, we explain how to make decisions in situations with user uncertainty - a realistic situation when a decision maker cannot always decide which alternative is better for him or her.

Title: Artificial Intelligence and Big Data management: the dynamic duo for moving forward data centric sciences

Abstract: After vivid discussions led by the emergence of the buzzword “Big Data”, it seems that industry and academia have reached an objective understanding about data properties (volume, velocity, variety, veracity and value), the resources and “know how” it requires, and the opportunities it opens. Indeed, new applications promising fundamental changes in society, industry and science, include face recognition, machine translation, digital assistants, self-driving cars, ad-serving, chat-bots, personalized healthcare, smart industry and more. The first lesson of the era of “Big Data” is that it is possible to access and exploit representative “samples” of available data collections thanks to the availability of the necessary resources for storing it and running greedy processing tasks on it. The second lesson is that computer science and mathematics disciplines must generate synergy with other sciences in order to exploit these new available “value”. The consequence is the emergence of “new” data centric sciences: data science, digital humanities, social data science, network science, computational science. These sciences with their new requirements and challenges call for a need to revisit the fundaments of databases, artificial intelligence and other disciplines used for addressing them with new perspectives. This novel and multidisciplinary data centric and scientific movement, promises new and not yet imagined applications that rely on massive amounts of evolving data that need to be cleaned, integrated and analysed for modelling purposes. Yet, data management issues are not usually perceived as central. In this keynote I will explore the key challenges and opportunities for data management in this new scientific world, and discuss how a possible data centric artificial intelligence community can best contribute to these exciting domains. If the moto is not academic, huge numbers of dollars being devoted to related applications are moving industry and academia to analyse these directions.

Ángel Fernando Kuri Morales, ITAM, Mexico.

Title: Mining Text: A computational Intelligence Approach