Aim and Scope
Recent rapid growth of AI has shown the potential to revolutionize most of the everyday aspects of human lives. The field of AI is traditionally divided into a number of subfields such as Machine Learning, Knowledge and Reasoning, Planning and Scheduling, SAT solving, Computer Vision (and others) that are usually pursued individually. But the challenges of real-world applications are often too hard for a single AI approach. Hence there is a need for Composite AI, which integrates several different AI approaches that complement each other to solve the problem. Development of Composite AI system is still ad-hoc and premature.
The workshop aims at bringing together researchers and practitioners from different AI subfields to discuss challenges that they currently face and to initiate a discussion about the benefits and challenges of Composite AI.
Submission Instructions
All papers must be submitted in a PDF format and must conform to the (IJCAI formatting).The extra page can only be used for acknowledgements and references. The reviewing process will be single-blind.
The submission is done via EasyChair at https://easychair.org/conferences/?conf=compai2025
Accepted Papers
Michael Youngblood, Filip Dvorak, Slavomir Svancar, Tomas Balyo and Michal Ficek:
Graph-Based Orchestration of Heterogeneous AI Models: A Control Node Approach to Composite Intelligence - Paper
Junhyung Moon, Seunggwan Hong, Eunkyeong Lee, Yunho Lim, Wanjin Park and Hyunseung Choo:
A Mixture-of-Agents Framework for EV Battery Diagnostics: Semantic Clustering and Prompt Engineering for Automated Reporting - Paper
Zelin Wan, Nithin Alluru, Jin-Hee Cho, Mu Zhu, Ahmed Anwar, Charles Kamhoua and Munindar Singh:
DT-Guided DRL: A Transition from Utility-based Decision Theory to Deep Reinforcement Learning - Paper
Benjamin Coriat and Eric Benhamou:
ALPHA: Advanced Learning for Portfolio Handling Applications - Paper
Luis Palacios, Matteo Morelli, Gael de Chalendar, Mykola Liashuha, Jaonary Rabarisoa, Lucas Labarussiat and Raphael Lallement:
Bridging Natural Language Understanding, Symbolic Planning, and Robotic Execution through Hybrid AI Systems - Paper
Liliane-Caroline Demers and Gilles Pesant:
Music Generation with Long-Term Structure Using Constraint Programming and Transformer-Based Decoders - Paper
Marianne Defresne, Romain Gambardella, Sophie Barbe and Thomas Schiex:
Symbol Grounding for Discrete Graphical Models through Data Imputation - Paper
