CAEPIA 2024 | XX EDITION

The Conference of the Spanish Association for Artificial Intelligence (CAEPIA) is a biennial forum open to worldwide researchers to present and discuss their last scientific and technological advances in Artificial Intelligence. The 20th edition, CAEPIA'24, will be held in A Coruña, Spain, from the 19th to the 21st June, 2024. Organized by the Laboratorio de Investigación y Desarrollo en Inteligencia Artificial (LIDIA) research group.

As in previous editions, the objectives are: to facilitate the dissemination of new ideas and experiences, to strengthen the links among the different research groups involved, to promote knowledge transfer between junior researchers and consolidated groups, and to help spread new developments to society. To achieve the proposed objectives, the authors are requested to send original unpublished works, which describe relevant research about topics related to Artificial Intelligence from all points of view: formal, methodological, technical or applied.

Original and unpublished works can be published in Lecture Notes in Artificial Intelligence or in the CAEPIA Proceedings, as well as already published highlighted works (key works). Read more about the type of contributions. All the submission and reviewing process will be done through the platform EasyChair

Chairs

General Chair

• Amparo Alonso Universidade da Coruña
• Bertha Guijarro Universidade da Coruña

Chairwoman of the awards committee

• Eva Onaindía Universidad Politécnica de Valencia

Chairs of Tutorials and Workshops

• Óscar Fontenla Universidade da Coruña

Chairman of General Session CAEPIA

• Óscar Fontenla Universidade da Coruña

Chairmen of Competitions

• Alberto Bugarín Universidad de Santiago de Compostela
• Jose Antonio Gámez Universidad de Castilla la Mancha

Editor of the LNAI Proceedings of CAEPIA

• Elena Hernández Universidade da Coruña
• Verónica Bolón Universidade da Coruña

Area Chairs

Topics

• AMBIENT INTELLIGENCE AND SMART ENVIRONMENTS
• Intelligent Sensor data fusion and collaboration in multi-sensor systems and networks
• Use of mobile, wireless, visual, and multi-modal sensor networks in intelligent systems
• Mobile/wearable intelligence
• Self-adaptive AmI systems
• Context awareness
• Cognitive and emotional awareness
• Behavior modeling
• Intention recognition
• Scene and event modeling, representation, and reconstruction
• Applications in health care, smart homes and smart buildings
• Modeling environments (homes, hospitals, transportation, roads, offices)
• COMPUTER VISION AND ROBOTICS
• Image / video analysis
• Biomedical Image analysis
• Activity / behavior recognition
• Feature extraction, grouping and segmentation
• Perception systems
• Biometrics
• Robot control
• Mobile robotics
• Micro robots and micro-manipulation
• Localization, navigation and mapping
• CONSTRAINTS, SEARCH AND PLANNING
• A.I. in Planning Games
• Constraint Optimization
• Constraint Satisfaction
• Dynamic Programming
• Heuristic Search
• Hierarchical Task Networks
• Markov Decision Processes
• Partially Observable Markov Decision Processes (POMDPs)
• Real Time Planning
• Satisfiability
• Scheduling
• Theoretical Foundations of Planning
• CREATIVITY AND ARTIFICIAL INTELLIGENCE
• Artificial intelligences based Art creations
• Artificial Intelligence based Music
• Artificial intelligence and literature/news generation
• Artificial intelligence creativity
• EDUCATION AND A.I.
• Educational data mining
• Machine Learning in Assisted Learning Systems
• Collaborative learning environments
• Virtual learning agents and virtual colleagues
• Smart teaching systems and simulations
• Smart teaching systems and gamification
• Student modeling
• Standards, authoring tools and development methodologies
• Technologies for specific learning domains
• EXPLAINABLE AND RESPONSIBLE A.I.
• Transparency in artificial intelligence models
• Post-Hoc Explicability Techniques for Artificial Intelligence Models
• Ethics in data-based learning
• Traceability of artificial intelligence models
• Reliability of learning artificial intelligence models
• Detection and treatment of bias in artificial intelligence data and models
• Methodology for an ethical and responsible use of artificial intelligence
• Security and data privacy in artificial intelligence models
• Neuro-symbolic reasoning to explain data-driven knowledge
• Evaluation of the interpretability of artificial intelligence models
• Creation of counter-examples for the inspection of artificial intelligence models
• Explicability and data fusion
• FOUNDATION, MODELS AND APPLICATIONS OF A.I.
• Foundations on Artificial Intelligence
• Artificial Intelligence based models
• Artificial Intelligence based Applicadtions
• Cognitive aspects of Artificial Intelligence
• Emergent Artificial Intelligence topics
• Artificial Intelligence and Philosophy
• FUZZY LOGIC
• Fundamentals of Fuzzy Logic
• Uncertainty modeling
• Knowledge acquisition and representation
• Approximate reasoning
• Decision making
• Information aggregation models and techniques
• Fuzzy databases
• Fuzzy logic and data mining
• Information retrieval
• Smart systems on the web
• Computing with words
• System modelling
• Fuzzy control
• Hardware for fuzzy logic
• Applications
• INTELLIGENT WEB AND INFORMATION RETRIEVAL
• Answer Search Systems
• Digital Libraries
• Information Extraction
• Information Integration
• Information Retrieval
• Recommender Systems
• Semantic web
• Web mining
• Web 2.0
• KNOWLEDGE REPRESENTATION, REASONING AND LOGIC
• Action, Change and Causality
• Computational Argumentation
• Automated Reasoning
• Knowledge Representation
• Computational Logic
• Description Logics and Ontologies
• Preferences and Beliefs
• Logic Programming
• Case-Based Reasoning
• Model-Based Reasoning
• Qualitative Reasoning
• Spatial and Temporal Reasoning
• Diagnosis and Abductive Reasoning
• Nonmonotonic Reasoning
• Knowledge Representation
• MACHINE LEARNING
• Clustering
• Classification
• Feature Selection
• Bayesian Networks and Markov Networks
• Learning from different types of data
• Machine Learning in non-standard situations
• Data reduction and/or transformation
• Learning from big data
• Machine Learning Applications
• MULTI-AGENT SYSTEMS
• Adaptation and self-organization
• Agent-Based Architectures and Programming
• Agent-Based Simulation and Emergent Behavior
• Agent Communication Languages
• Agreement Technologies (coordination, negotiation, argumentation, rules, confidence)
• Methodologies and Infrastructures (platforms, tools, environment)
• Social, Organizing and Institutional Approximations
• Agent-Based Modeling
• NATURAL-LANGUAGE PROCESSING
• Syntactic Analysis and Grammatical Inference
• Text Classification and Subjects
• Automatic Abstract Generation
• Lexical Disambiguation of Words
• Discourse, Dialogue and Pragmatics
• Text Mining
• Natural Language Modeling
• Natural Language Processing
• Multilingual Language Processing
• Speech Recognition
• Question Answering
• Machine Translation
• ONTOLOGIES AND KNOWLEDGE GRAPHS
• Linked Open Data
• Knowledge Graphs
• High level and domain specific ontologies
• Ontology driven information systems
• Ontology Alignment
• Ontology and Experimental Data
• OPTIMIZATION AND SEARCH
• Applications of search and Optimization
• Bio-inspired Methods
• Hybrid Algorithms
• Mathematical Programming
• Metaheuristics
• Optimization, Search and Learning
• Parallel Algorithms
• Local and Global Optimization
• Theory of Search and Optimization
• UNCERTAINTY IN A.I.
• Approximate Reasoning
• Bayesian Networks
• Decision/Utility Theory
• Exact and Approximate Probabilistic Inference
• Modeling, Inference, Learning and Decision Making under Uncertainty
• Preference Elicitation
• Probabilistic Graphical Models

Program Committee