🔍 The Workshop Scope
The LoStaN workshop aims to bring together researchers and practitioners interested in bridging the gap between two traditionally distinct paradigms in Artificial Intelligence: symbolic reasoning based on logical knowledge, and data-driven approaches grounded in statistics and (deep) machine learning.
During its history, AI has seen tremendous progress from both ends of this spectrum. Symbolic methods offer interpretability, generalizability, and the ability to incorporate structured domain knowledge, while neural and statistical techniques excel in learning from vast amounts of data, dealing with uncertainty, and scaling to complex tasks. However, unifying these paradigms remains a grand challenge. The workshop aims to foster a research community that sees logical reasoning and statistical learning not as competing paradigms, but as complementary facets of intelligent behavior, and their integration not only as a technical challenge but rather as a transformative opportunity.
LoStaN provides a forum for discussing foundational questions, novel methodologies, and practical applications that seek to integrate logical and statistical AI, with the aim to energize this interdisciplinary space, promote collaboration between research communities, and inspire innovative solutions to AI.