|Títol||Working Papers of the IJCAI-ECAI-2018 Workshop on Learning and Reasoning|
|Publication Type||Conference Proceedings|
|Year of Conference||2018|
|Authors||Vaishak B, Godo L, Prade H, Renz J, Schockaert S, Schmid U, Wolter D|
|Conference Name||IJCAI-ECAI-2018 Workshop on Learning and Reasoning: Principles & Applications to Everyday Spatial and Temporal Knowledge|
|Conference Location||Stockholm (Sweden)|
Knowledge representation and reasoning (KRR), on the one hand, and machine learning (ML), on the other hand, have largely been developed as independent research trends in artificial intelligence (AI). Human reasoning, however, is often based on an intricate combination of processes that are related to learning (e.g. induction or extrapolation) and processes that are closer to deductive reasoning. Similarly, we can expect that progress in AI will increasingly need to rely on hybrid approaches that combine the explainability and teachability of KRR methods with the robustness and data-driven nature of ML methods. The ambitious aim of truly integrating reasoning and learning beyond one-way linkage raises many new questions, which this workshop hopes to explore.
Beyond a study of the underlying principles, this workshop also focuses on applications, with a particular emphasis on the use of spatial and temporal knowledge in everyday tasks.
The workshop serves as a forum for researchers from di↵erent fields (in- cluding Automated Theorem Proving, Cognitive Computing, Cognitive Ro- botics, Commonsense Reasoning, Constraint Solving, Logic, Mathematics, Machine Learning, Natural Language Processing, Theoretical Computer Sci- ence, Qualitative Reasoning) to discuss open problems, methodology, and recent advancements in the field. It also provides a forum for early career researchers to present their current work and to build up networks.
This workshop is the first under this name and with this scope. However it is to a limited extent a follow-up of previous ECAI and IJCAI workshops (already co-organised by three of the co-organisers of the present workshop):
• the successful series of WL4AI workshops (Weighted Logics for Ar- tificial Intelligence: ECAI-2012, IJCAI-2013, IJCAI-2015)
• the IJCAI-2017 workshop on Logical Foundations for Uncertainty and Learning (LFU)
L & R - 2018 looks broadly at the intersection of logical formalisms and learning, by unifying the themes of WL4AI and LFU, and additionally en- couraged submissions touching on defeasible reasoning and nonmonotonic frameworks among other issues.
Finally, we would like to express our gratitude to:
- Quant a IIIA