The Conference of the Spanish Association for Artificial Intelligence (CAEPIA) is a biennial forum open to researchers worldwide to present and discuss their latest scientific and technological advances in Artificial Intelligence (AI). Authors are invited to submit original unpublished works describing relevant research related to Artificial Intelligence from all perspectives: formal, methodological, technical, or applied.

Contact: caepia2026@easychair.org

CAEPIA seeks to promote quality by giving special visibility to works highlighted by reviewers. For this purpose, awards will be granted in all events we organize, allowing both emerging and established researchers to showcase their efforts in producing impactful research. Awards will be granted based purely on scientific criteria and will consist of an accreditation diploma along with a financial reward, which may vary depending on the event.

Within CAEPIA, the Doctoral Consortium is organized as a forum for PhD students to interact with other researchers through the discussion of their thesis projects.

With the aim of highlighting the academic and practical importance of AI in university studies, the Bachelor’s Final Thesis and Master’s Final Thesis competition based on AI techniques is announced.

Additionally, this edition of CAEPIA will include outstanding works (Key Papers) already published in prestigious journals or forums.

At CAEPIA’26, several federated conferences and workshops will be held, each with its own program committee and individual call for papers.

Types of contributions

All contributions must be submitted through EasyChair.

  • Submission of papers for publication in Lecture Notes in Artificial Intelligence (LNAI): Papers submitted for publication in a volume of Springer’s Lecture Notes series must be written in English and will undergo a double-blind review process. Contributions for LNAI may have a maximum length of 12 pages and must follow the format specified in the LNCS guidelines (available in Word and LaTeX2e). The submitted paper must describe original research work with solid, well-founded, and demonstrable results in any topic of the conference. Publication in LNCS proceedings will be included in the Lecture Notes in Artificial Intelligence series (LNCS/LNAI Home Page). Registration of one of the authors and submission of the consent form for publication in LNCS will be required. When preparing and submitting your proposal, please take into account the following documents of interest:

    Author guidelinesLNCS Consent to Publish Form

  • Submission of papers for publication in CAEPIA Proceedings: In this case, submitted and accepted papers will be published in the CAEPIA proceedings or in the proceedings of the corresponding federated conference. These papers may have a maximum length of 12 pages and must follow the LNCS guidelines (available in Word and LaTeX2e). The submitted paper must describe original research with solid, well-founded, and demonstrable results in any topic of the corresponding conference. Registration of one author is required.

  • Outstanding already published works (Key Papers): Recent papers published in prestigious journals or forums between 2024 and 2026. The goal is to disseminate them among a broad audience of the AI community, providing members of the community the opportunity to learn about works they may not be familiar with and fostering interdisciplinarity. Papers must be submitted in LNCS format (available in Word and LaTeX2e) with a maximum length of 4 pages, clearly referencing the previously published work. Registration of one author is required.

  • Doctoral Consortium projects: Submission of preliminary doctoral work is encouraged. These works will be presented in special sessions during the conference. The goal is to promote fruitful discussion between the candidate and the audience. These works may have a maximum length of 12 pages and must follow the LNCS guidelines (available in Word and LaTeX2e). Submission must be made through the CAEPIA’26 EasyChair page (Doctoral Consortium track). More information at Doctoral Consortium.

  • Submission of documents for the Frances Allen Award: This award aims to highlight the outstanding work of female students, professors, and researchers to serve as inspiration for future female students in Computer Science studies. Each candidate must submit a document of up to 6 pages formatted according to the LNCS guidelines (available in Word and LaTeX2e). More information at Frances Allen Award.

  • AI-based Bachelor’s and Master’s thesis competing for the CAEPIA award, according to the competition rules. The documentation to be submitted shall consist of a document of no more than 5 pages in LNCS-Springer Computer Science Proceedings format. More information at Bachelor’s and Master’s Award.

Accepted papers will be assigned a 15-minute time slot at the conference, including oral presentation and questions.

Topics of interest

Ambient Intelligence and Smart Environments
  • Applications in healthcare, smart homes and smart buildings
  • Behaviour modelling
  • Cognitive and emotional awareness
  • Context awareness
  • Environment modelling (homes, hospitals, transport, roads, offices)
  • Intention recognition
  • Intelligent sensor data fusion and collaboration in multisensor systems and networks
  • Mobile/ubiquitous intelligence
  • Modelling, representation and reconstruction
  • Self-adaptive AmI systems
  • Use of mobile, wireless, visual and multimodal sensor networks in intelligent systems
Computer Vision & Robotics
  • Activity/behaviour recognition
  • Biomedical image analysis
  • Biometrics
  • Feature extraction, clustering and segmentation
  • Image/video analysis
  • Localization, navigation and mapping
  • Micro robots and micro-manipulation
  • Mobile robotics
  • Perception systems
  • Robot control
Constraints, Search and Planning
  • AI 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
  • AI and news/literature generation
  • AI-based artistic creations
  • AI-based music generation
  • Creative Artificial Intelligence
Education and Artificial Intelligence
  • Collaborative learning environments
  • Educational data mining
  • Intelligent tutoring systems and gamification
  • Intelligent tutoring systems and simulation
  • Machine learning in computer-assisted education systems
  • Standards, authoring tools and development methodologies
  • Student modelling
  • Technologies for specific learning domains
  • Virtual pedagogical agents and virtual companions
Explainable and Responsible Artificial Intelligence
  • Detection and treatment of bias in data and AI models
  • Ethics in data-driven learning
  • Evaluation of AI model interpretability
  • Explainability and data fusion
  • Generation of counterexamples for model inspection
  • Methodologies for ethical and responsible use of AI
  • Neuro-symbolic reasoning for explaining data-based knowledge
  • Post-hoc explainability techniques for AI models
  • Reliability of AI model learning
  • Security and data privacy in AI models
  • Traceability of AI models
  • Transparency in AI models
Foundations, Models and Applications of AI
  • AI-based applications
  • AI-based models
  • Artificial Intelligence and Philosophy
  • Cognitive aspects of Artificial Intelligence
  • Emerging topics in Artificial Intelligence
  • Foundations of Artificial Intelligence
Fuzzy Logic
  • Applications
  • Approximate reasoning
  • Computing with words
  • Decision making
  • Foundations of fuzzy logic
  • Fuzzy control
  • Fuzzy databases
  • Fuzzy logic and data mining
  • Hardware for fuzzy logic
  • Information aggregation models and techniques
  • Information retrieval
  • Intelligent web systems
  • Knowledge acquisition and representation
  • Systems modelling
  • Uncertainty modelling
Intelligent Web and Information Retrieval
  • Digital libraries
  • Information extraction
  • Information integration
  • Information retrieval
  • Question answering systems
  • Recommender systems
  • Semantic web
  • Web 2.0
  • Web mining
Knowledge Representation, Reasoning and Logic
  • Action, change and causality
  • Automated reasoning
  • Case-based reasoning
  • Computational argumentation
  • Computational logic
  • Description logic and ontologies
  • Diagnosis and abductive reasoning
  • Knowledge representation
  • Logic programming
  • Model-based reasoning
  • Non-monotonic reasoning
  • Preferences and beliefs
  • Qualitative reasoning
  • Spatial and temporal reasoning
Machine Learning
  • Bayesian networks and Markov networks
  • Classification
  • Clustering
  • Data reduction and/or transformation
  • Feature selection
  • Learning from different data types
  • Learning from large-scale data (big data)
  • Machine learning applications
  • Machine learning in non-standard situations
Multiagent Systems
  • Adaptation and self-organization
  • Agent-based architectures and programming
  • Agent-based models
  • Agent-based simulation and emergent behaviour
  • Agent communication languages
  • Agreement technologies (coordination, negotiation, argument, rules, trust)
  • Methodologies and infrastructures (platforms, tools, environments)
  • Social, organizational and institutional approaches
Natural Language Processing
  • Automatic summarization
  • Discourse, dialogue and pragmatics
  • Machine translation
  • Multilingual language processing
  • Natural language modelling
  • Natural language processing
  • Question answering
  • Speech recognition
  • Syntactic analysis and grammatical inference
  • Text classification and topic detection
  • Text mining
  • Word sense disambiguation
Ontologies and Knowledge Graphs
  • Knowledge graphs
  • Linked open data
  • Ontologies and experimental data
  • Ontology alignment
  • Ontology-based information systems
  • Upper-level and domain ontologies
Search and Optimization
  • Bio-inspired methods
  • Hybrid algorithms
  • Local and global optimization
  • Mathematical programming
  • Metaheuristics
  • Optimization, search and learning
  • Parallel algorithms
  • Search and optimization applications
  • Search and optimization theory
Uncertainty in AI
  • Approximate reasoning
  • Bayesian networks
  • Decision/Utility theory
  • Exact and approximate probabilistic inference
  • Modelling, inference, learning and decision making under uncertainty
  • Preference elicitation
  • Probabilistic graphical models

Important Dates

🗓️ March

  • Mar 15 — Workshops (Proposal submission deadline)

🗓️ April

  • Apr 30 — LNAI Papers

    Notification: June 1
    Final version: June 15

🗓️ May

  • May 15 — Key Papers

    Notification: June 17
    Final version: July 3

  • May 15 — CAEPIA Proceedings Papers

    Notification: June 17
    Final version: July 3

  • May 15 — Doctoral Consortium

    Notification: June 17
    Final version: July 3

  • May 15 — TFG and TFM Competition

    Notification: June 17
    Final version: July 3

  • May 15 — Frances Allen Award

    Notification: June 17

Contribution Submission

Submission of papers to CAEPIA’26 requires prior registration in the EasyChair portal. CAEPIA’26 submissions will be reviewed by members of the Program Committee, supervised by an area coordinator.

Submission of contributions to EasyChair.

Proceedings

Accepted papers will be published in several CAEPIA proceedings volumes delivered to all attendees in electronic format. Papers accepted for LNAI will be accessible in the corresponding Springer volume.

Call for Participation (CfP)

Participate in CAEPIA’26.

Download the CFP