9 Dec 2016
Barcelona, Spain
**************************************************** Cognitive Computation: Integrating Neural and Symbolic Approaches (CoCo @ NIPS 2016) **************************************************** Workshop at NIPS 2016, Barcelona, Spain December 09, 2016 == WORKSHOP WEBPAGE == http://www.neural-symbolic.org/CoCo2016/ == MISSION STATEMENT == While early work on knowledge representation and inference was primarily symbolic, the corresponding approaches subsequently fell out of favor, and were largely supplanted by connectionist methods. In this workshop, we will work to close the gap between the two paradigms, and aim to formulate a new unified approach that is inspired by our current understanding of human cognitive processing. This is important to help improve our understanding of Neural Information Processing and build better Machine Learning systems, including the integration of learning and reasoning in dynamic knowledge-bases, and reuse of knowledge learned in one application domain in analogous domains. The workshop brings together established leaders and promising young scientists in the fields of neural computation, logic and artificial intelligence, knowledge representation, natural language understanding, machine learning, cognitive science and computational neuroscience. Invited lectures by senior researchers will be complemented with presentations based on contributed papers reporting recent work (following an open call for papers) and a poster session, giving ample opportunity for participants to interact and discuss the complementary perspectives and emerging approaches. The workshop targets a single broad theme of general interest to the vast majority of the NIPS community, namely translations between connectionist models and symbolic knowledge representation and reasoning for the purpose of achieving an effective integration of neural learning and cognitive reasoning, called neural-symbolic computing. The study of neural-symbolic computing is now an established topic of wider interest to NIPS with topics that are relevant to almost everyone studying neural information processing. == KEYWORDS == The following list gives some (but by far not all) relevant keywords for the CoCo @ NIPS 2016 workshop: - neural-symbolic computing; - language processing and reasoning; - cognitive agents; - multimodal learning; - deep networks; - knowledge extraction; - symbol manipulation; - variable binding; - memory-based networks; - dynamic knowledge-bases; - integration of learning and reasoning; - explainable AI. == CALL FOR PAPERS == We invite submission of papers dealing with topics related to the research questions discussed in the workshop. The reported work can range from theoretical/foundational research to reports on applications and/or implemented systems. We explicitly also encourage the submission of more controversial papers which can serve as basis for open discussions during the event. Possible topics of interest include but are (by far!) not limited to: - The representation of symbolic knowledge by connectionist systems; - Neural Learning theory; - Integration of logic and probabilities, e.g., in neural networks, but also more generally; - Structured learning and relational learning in neural networks; - Logical reasoning carried out by neural networks; - Integrated neural-symbolic approaches; - Extraction of symbolic knowledge from trained neural networks; - Integrated neural-symbolic reasoning; - Neural-symbolic cognitive models; - Biologically-inspired neural-symbolic integration; - Applications in robotics, simulation, fraud prevention, natural language processing, semantic web, software engineering, fault diagnosis, bioinformatics, visual intelligence, etc. - Approaches/techniques making AI and/or Machine Learning systems/algorithms better explainable or increasing human comprehensibility. = Submission instructions = - Submissions have to be made via EasyChair ( https://easychair.org/conferences/?conf=coconips2016) before the paper submission deadline indicated below. - Submissions are limited to at most eight pages, an additional ninth page containing only cited references is allowed. Still, also shorter papers are expressly welcomed. - Submissions have to use the NIPS 2016 submission format (see http://nips.cc/Conferences/2016/PaperInformation/StyleFiles). - Reviewing will be single-blind, i.e., you are free to indicate your name etc. on the paper. (Still, this is not an obligation.) Please note that at least one author of each accepted paper must register for the event and be available to present the paper at the workshop. =Publication= Accepted papers will be published in official workshop proceedings submitted to CEUR-WS.org. Authors of selected papers will be invited to submit a revised and extended version of their papers to a journal special issue after the workshop. == IMPORTANT DATES == - Deadline for paper submission: October 10, 2016 - Notification of paper acceptance: October 30, 2016 - Camera-ready paper due: November 14, 2016 - Workshop date: December 09, 2016 - NIPS 2015 main conference: December 5-8, 2016 == ADMISSION == The workshop is open to anybody, please register via NIPS 2016 ( http://nips.cc). == WORKSHOP ORGANIZERS == - Tarek R. Besold (University of Bremen, Germany) - Antoine Bordes (Facebook AI Research, USA) - Artur d'Avila Garcez (City University London, UK) - Greg Wayne (Google DeepMind, UK) == ADDITIONAL INFORMATION == - General questions concerning the workshop should be addressed to Tarek R. Besold at Tarek(dot)Besold(at)uni(hyphen)bremen(dot)de. - This workshop is conceptually related to the series of International Workshops on Neural-Symbolic Learning and Reasoning (NeSy). If interested, have a look at http://www.neural-symbolic.org - Please also feel free to join the neural-symbolic integration mailing list for announcements and discussions - it's a low traffic mailing list. If interested, register at http://maillists.city.ac.uk/mailman/listinfo/nesy . -- [LOGIC] mailing list http://www.dvmlg.de/mailingliste.html Archive: http://www.illc.uva.nl/LogicList/ provided by a collaboration of the DVMLG, the Maths Departments in Bonn and Hamburg, and the ILLC at the Universiteit van Amsterdam