Cognitum 2018 - Fourth Workshop on Cognitive Knowledge Acquisition and Applications

To facilitate natural and fruitful interaction with humans, cognitive systems must be able to learn, reason, and communicate in natural language. Ultimately, this interaction aims to extend and enhance human cognition, not by having cognitive systems operate as subsidiary workers that solve problems for humans, but by having cognitive systems act as expert assistants able to collaborate with humans and provide them with help in a form compatible with how humans naturally process and understand information.
Knowledge acquisition is central to the design of such cognitive systems. Knowledge should be in a form that allows cognitive systems to understand natural language questions, perform reasoning to answer questions, and explain their reasoning. Unlike the significant body of work on mining the web for facts or answers to specific questions (such as NELL and IBM’s Watson Jeopardy! system), the workshop’s emphasis is on the acquisition of general knowledge that can be applied by cognitive systems in novel situations to perform reasoning. At the same time, acquired knowledge should be cognitive knowledge, which exhibits characteristics similar to human knowledge and allows systems to explain their reasoning.
We welcome ongoing and exciting preliminary work. Topics of interest include, but are not limited to:
Integrating natural language processing with knowledge representation and reasoning.
Acquiring cognitive knowledge (knowledge in a form that supports explanation to humans).
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 natural language processing, perception, and reasoning.
Alternative acquisition methods (such as crowdsourcing).
Acquisition from media other than text (such as video).
Architecture and implementation of cognitive systems.
Real-world applications that utilize cognitive knowledge.