Dear colleagues, The deadline for submissions to Cognitum 2017 has been extended to May 27th, 2017.
The emphasis of the workshop in on the acquisition of general knowledge in a way that allows cognitive systems to explain, and to be explained to. We welcome work that investigates how symbolic learning, deep learning, or other existing or novel knowledge acquisition approaches can help materialize this goal. A short CFP follows. Regards, Loizos ------------------------------------------------------------------------------------------------------------------ 3rd Workshop on Cognitive Knowledge Acquisition and Applications (Cognitum 2017) ------------------------------------------------------------------------------------------------------------------ 3rd CALL FOR PAPERS --- Final Submission Deadline: May 27th, 2017 --- Held in conjunction with IJCAI 2017, Melbourne, Australia (collocated with ICML, SAT, CP, UAI, ICLP, AGI, AI & ML Summit) More information: http://cognitum.ws/ --- Travel Support --- We expect to have grants (for students and early-stage researchers) to partially subsidize participation in the workshop. More information will be posted on the workshop website at a later date. --- Keynote Talk --- Mary-Anne Williams, Distinguished Professor and Director of Disruptive Innovation, University of Technology Sydney (UTS) --- Short Description --- Knowledge acquisition is central to the design of cognitive systems. The workshop's emphasis is on the acquisition of general knowledge that can be applied by a cognitive system in novel situations to elaborate what has been sensed with plausible and useful inferences. At the same time, the process of knowledge acquisition should exhibit characteristics akin to those of human learning, allowing the cognitive systems to explain their inferences and accept user feedback to improve their performance. We welcome contributions that take a position and discuss the merits of simple and intuitive acquisition processes that could potentially err more versus the merits of acquisition processes that use computationally-heavy machinery to improve performance at the expense of psychological validity. Topics of interest include, but are not limited to: - Formal frameworks for acquiring cognitive knowledge. - Deep learning for acquiring cognitive knowledge. - Principled evaluation of acquired cognitive knowledge. - Psychologically-guided design of the acquisition process. - Considerations related to scalability and parallelization. - Active choice among available learning data/resources. - Representation languages for cognitive knowledge. - Static versus temporal/causal cognitive knowledge. - Interaction of acquisition with perception and reasoning. - Alternative acquisition methods (e.g., crowdsourcing). - Acquisition from media other than text (e.g., video). - Architecture and implementation of cognitive systems. - Real-world applications that utilize cognitive knowledge. Special theme: Intelligent Assistants: Explaining Inferences and Accepting User Feedback ------------------------------------------------------------------------------------------------------------------ _______________________________________________ RuleML-all mailing list [email protected] http://ruleml.org/mailman/listinfo/ruleml-all_ruleml.org
