EPIA’17 invites submissions to the Doctoral Symposium on Artificial Intelligence, SDIA. The goal of this symposium is to provide an informal environment where students in early stages of their doctoral research can present their main research ideas and discuss them with other students and the senior scientific community. The main advantages of SDIA’17 are three-fold:

• Students obtain feedback from the scientific community, event in an early stage of the doctoral research.
• To give students the opportunity to present their work in an informal environment, as a preparation to future presentations in international workshops and conferences.
• Students have the opportunity to know the work of other students that are in the same stage of doctorial work and that have similar research interests.

SDIA is promoted by APPIA – Associação Portuguesa para a Inteligência Artificial (Portuguese Association for Artificial Intelligence), and it aims at improving the quality of Ph.D. thesis in Artificial Intelligence.

Important Dates

Paper submission deadline: june 15, 2017

Author notification: july 15, 2017

Deadline for final camera ready copies: july 25, 2017

Submission

SDIA’17 accepts the submissions of full papers, short-papers, position papers or thesis proposals. Submitted papers should be prepared according to the Springer LNCS format, with a maximum of 12 pages. The papers must include the following: title, author, Ph.D. advisor(s), abstract, keywords, starting date and estimated conclusion date of Ph.D.

All papers should be submitted in PDF format through the EPIA 2017 EasyChair submission page.

Accepted submissions will be published in the SDIA Symposium, a APPIA edition with ISBN.

Accepted submissions will also be invited to present a poster at the BAAI poster session, where students will be able to interact with companies interested in hiring AI experts.

Special Conditions

Students with accepted papers in the SDIA / BAAI poster session may have a reduced registration fee. Please check the Registration page at /registration/.

Organization

Goreti Marreiros, Instituto Superior de Engenharia do Porto, Portugal

Joana Urbano, University of Porto, Portugal

Program Committee

Alberto Fernandez (University Rey Juan Carlos, Spain)

Altigran  S. Da Silva (Universidade Federal do Amazonas, Brazil)

Amílcar Cardoso (University of Coimbra, Portugal)

Ana Paiva (INESC, Lisbon)

Ana Paula Rocha (University of Porto, Portugal)

Carlos Soares (University of Porto, Portugal)

Charlotte Gerritsen (VU University Amsterdam, Holland)

Daniel Castro Silva (University of Porto, Portugal)

Eugénio Oliveira (University of Porto, Portugal)

Francisco Pereira (Instituto Superior de Engenharia de Coimbra, Portugal)

Goreti Marreiros (Instituto Superior de Engenharia do Porto, Portugal)

Joana Urbano (University of Porto, Portugal)

Leonardo Trujillo (Instituto Tecnológico de Tijuana, Mexico)

Luís Correia (University of Lisbon, Portugal)

Luis Paulo Reis (University of Minho, Portugal)

Miguel Rocha (University of Minho, Portugal)

Minh Dao-Tran (Institute of Information Systems, Vienna University of Technology, Austria)

Paulo Novais (University of Minho, Portugal)

Penousal Machado (University of Coimbra, Portugal)

Shinichi Konomi (University of Tokyo, Japan)

Vítor Santos Costa (University of Porto, Portugal)

Topics of Interest

The main topics of interest include, but are not restricted to:

• Activity Recognition
• Agents and Multiagent Systems
• AI and Medicine
• AI and Law
• AI and the Web
• AI Architectures
• Ambient Intelligence
• Applications of AI
• Automated Reasoning
• Bio-Informatics
• Cognitive Sciences
• Collaborative Networks
• Computational Biology
• Computational Sustainability
• Computer Vision and Pattern Recognition
• Constraint Programming
• Control
• Data Mining, Text Mining and Web Mining
• Description Logics
• e-Commerce and e-Business
• e-Learning and Intelligent Tutoring
• Evolutionary Computation
• Fuzzy Logic
• Game Playing
• Game Theory
• Graphical Models
• Human Computer Interaction
• Human Robot Interaction
• Information Retrieval
• Knowledge Discovery
• Knowledge Representation and Reasoning
• Logic
• Machine Learning
• Multi-Robot Systems
• Natural Language
• Neural Networks
• Ontologies
• Optimization
• Plan Recognition, Execution and Monitoring
• Planning
• Preferences
• Probabilistic Reasoning
• Qualitative Reasoning
• Reinforcement Learning
• Relational Learning
• Robotics
• Scheduling
• Scientific Discovery
• Search
• Sensor Fusion
• Statistical Learning

Other Information

For more information, please refer to the Web pages of EPIA 2017 or to the Web pages of APPIA at http://www.appia.pt.