AIxIA 2021
WORKSHOPS
November 29-30, 2021
Online events
The growth of research and interests about AI today requires that specific communities of contributors could meet and face together in order to focus on specific fields of work. Due to the fact that the growing number of focused activities represents the richness of the entire AI community, AIxIA 2021 hosts a set of dedicated workshops which will be held on the two days before the starting of the Main Conference on November 29 - 30, 2021.
Each workshop organizes its own calls and provides the collection af accepted papers on CEUR proceedings. See the following list of accepted workshops for details and related information.
29/11/2021
Argumentation is the study of the processes and activities involving the production and exchange of arguments, where arguments are attempts to persuade someone or something by giving reasons for accepting a particular conclusion as evident. As such, argumentation provides procedures for making and explaining decisions and is able to capture diverse kinds of reasoning and dialogue activities in a formal but still intuitive way, enabling the integration of different specific techniques and the development of trustable applications.
For these reasons, over the last two decades formal argumentation has become a main research topic in AI. A variety of theoretical models at different levels of abstraction have been extensively studied, ranging from purely abstract models to concrete implemented systems, argumentation solvers have been developed to identify the justification status for arguments according to different semantics, and a variety of applications of argumentation have been proposed for several fields, ranging from modeling dialogues in social networks to law and medicine. Given that the study of argumentation is inherently interdisciplinary, the goal of our workshop is to stimulate discussions and promote scientific collaboration among researchers not only directly involved in argumentation, but also from research fields indirectly related to argumentation.
We celebrate the 10th edition of MLDM.it. Following the success of the first nine editions of the Italian Workshop on Machine Learning and Data Mining (MLDM.it) at the AI*IA Symposiums and AI*IA Conferences, this workshop aims at bringing together researchers actively involved in the fields of machine learning, data mining, deep learning, pattern recognition, and knowledge discovery. Besides traditional ML&DM technique presentations, the edition of this year focuses in particular on the presentation of new open problems and challenges for the ML&DM addressing the wider AI area and its applications, and on the discussion of issues related to the Italian researchers opportunities in the context of the new national and European scenario for the AI research networks.
The goal of the Natural Language for Artificial Intelligence (NL4AI) workshop is to explore the role of Natural Language, Natural Language Processing and Understanding in Artificial Intelligence problems and applications. We believe that new technological challenges and opportunities rise at the boundary between NLP and AI. On the one hand, AI applications benefit from a deeper understanding of Natural Language data, and thus the integration of advanced NLP methods. On the other hand, NLP benefits greatly from being used in wider areas of AI where problems and methodologies related to NL can be challenged and evaluated in new contexts. We encourage papers exploring the application of NLP approaches to tasks in specific AI areas, such as Robotics, Vision, Health, Cultural Heritage, Reasoning and so on. Moreover, we encourage papers exploring the application of NLP methods and models to specific domains and applications.
Medicine and health care require highly complex decision making to ensure that the trajectory a patient with a disease needs to take for diagnosis, treatment, recovery, and finally outcome is optimal in some sense. As a consequence, researchers have to draw methods from the entire field of AI.
On the other hand, health care and medicine are built upon a rich body of knowledge, e.g. concerning the pathophysiology of diseases, molecular, genetic, cytological, and histological characterization of stages of a disease, described by temporal and spatial disease patterns. Such knowledge can also act as background knowledge to guide machine learning.
This workshop aims at elucidating the relationship between what can be expected from AI methods when applied to health-care problems and the role knowledge of health care and clinical medicine can play in developing AI solutions to health-care and clinical problems.
AIxAS workshop aims to strengthen the forum of the members of the Italian Association for Artificial Intelligence, public institutions, and industrial realities on the topics of AI applied to the Ageing Society. It will collect knowledge, experiences and trends showing how AI could add value to the promotion of a new generation of innovative support systems. Contributions from cross-disciplinary approaches and stakeholders involved in the Ageing Society are also welcome, to support AI approaches to be a player in the future of AI for this social phenomenon.
RCRA is the workshop of the RCRA working group of the AIxIA. The main goal of the workshop is to provide a venue for exchanging ideas and proposing new benchmarks and experimentation methodologies for algorithms in Artificial Intelligence, with focus on "difficult" reasoning problems coming from different communities such as SAT, QBF, logic and constraint programming, planning, scheduling, and to propose applications based on such methodologies.
30/11/2021
We celebrate the 10th edition of MLDM.it. Following the success of the first nine editions of the Italian Workshop on Machine Learning and Data Mining (MLDM.it) at the AI*IA Symposiums and AI*IA Conferences, this workshop aims at bringing together researchers actively involved in the fields of machine learning, data mining, deep learning, pattern recognition, and knowledge discovery. Besides traditional ML&DM technique presentations, the edition of this year focuses in particular on the presentation of new open problems and challenges for the ML&DM addressing the wider AI area and its applications, and on the discussion of issues related to the Italian researchers opportunities in the context of the new national and European scenario for the AI research networks.
Causal-ITALY aims at bringing together researchers and practitioners in artificial intelligence, logic, and philosophy of science, with a dedicated focus on methods and trends emerging from the study of causality. In a socio-economical context rapidly moving towards an ethical use of robust artificial intelligence, causality stands out as a vastly important and needed feature. Causality directly supports what-if and counterfactual reasoning, fundamental components for any ethical, robust, and resilient use of artificial intelligence tools and systems. Indeed, much of the current research in artificial intelligence aims at predicting future events. However, no matter how sophisticated the predictive algorithms are, their users may fall into the trap of equating correlation with causation. This workshop welcomes papers on systems, tools, and applications of artificial intelligence methods for causal learning and reasoning, both logic-based and statistical. It encourages submissions presenting recent developments, including works in progress, as well as short summaries of recently published papers.
Artificial Intelligence systems are increasingly playing an increasingly important role in our daily lives. As their importance in our everyday lives grows, it is fundamental that the internal mechanisms that guide these algorithms are as clear as possible. It is not by chance that the recent General Data Protection Regulation (GDPR) emphasized the users' right to explanation when people face artificial intelligence-based technologies. Unfortunately, the current research tends to go in the opposite direction, since most of the approaches try to maximize the effectiveness of the models (e.g., recommendation accuracy) at the expense of the explainability and the transparency. The main research questions which arise from this scenario is straightforward: how can we deal with such a dichotomy between the need for effective adaptive systems and the right to transparency and interpretability? Several research lines are triggered by this question: building transparent intelligent systems, analyzing the impact of opaque algorithms on final users, studying the role of explanation strategies, investigating how to provide users with more control in the behavior of intelligent systems. The workshop tries to address these research lines and aims to provide a forum for the Italian community to discuss problems, challenges and innovative approaches in the various sub-fields of AI.
The workshop WEPO 2021 is intended to foster the discussion about Evolutionary Computation (EC) and Population-based Optimization (PO). Nature-inspired algorithms are largely used for solving optimization problems in a large number of fields due to their simplicity and effectiveness. The underlying principles behind these algorithms are simple enough to allow a great adaptability to various problems and domains and, while maintaining excellent effectiveness, they offer the possibility of obtaining explainable solutions. In a scenario where AI is increasingly predominant, but often with black box solutions, the explainability of EC and PO solutions may be an answer to the growing demand for understandable AI. The goal of this workshop is to explore and discuss the latest trends, promising results and hot topics in the fields of EC and PO, offering a discussion forum where new research collaborations can be established.
Automated Planning and Scheduling is a historical and active branch of Artificial Intelligence that concerns the realization of strategies or action sequences, typically for execution by intelligent agents, autonomous robots and unmanned vehicles.
The Italian workshop on Planning and Scheduling (IPS) aims at bringing together researchers interested in different aspects of planning and scheduling problems, and to introduce new researchers to the community.
The workshop welcomes both theoretical and practical contributions in any aspect of automated planning and scheduling, with the purpose of encouraging the Italian research community to share ideas and new trends on the field.
The forum is an occasion not only to consolidate the community, but also to engage young and new researchers into the field.
Artificial Intelligence is becoming crucial in every business field, even reshaping organizations and how technologies affect management and business. AI has the power to transform business and society, in a transversal and pervasive way, due to its ability to extract and manage knowledge potentially in every industry. This workshop will be focused on the current technological scenario of AI for business in heterogenous fields and industries. The workshop mainly aims at allowing organizations, academics, researchers, companies, decision-makers and practitioners to share and analyze heterogenous research works and business case studies dealing with AI in business fields. Companies will share specific case studies as well as their current issues AI is solving in their organizations. Researchers will provide scientific works and studies to contribute in the advancement of the many synergies between AI and business models and organizations. The final aim of the workshop is contributing in depicting the overall scenario and framework of the exploitation, advantages and current issues of AI in business.
AIRO 2021 is part of an on-going effort to consolidate the Italian community working on various aspects of the intersection between AI and Robotics. AIRO 2021 will advance current debates about the use of Artificial Intelligence techniques to design robots able to interact with real world environments. It will showcase contributions from the community working at the intersection between Artificial Intelligence and Robotics.