NeSy -- Neural-Symbolic Computation
About NeSy	English (USA)
Welcome to the Neural-Symbolic (NeSy) email list. NeSy is a low-traffic moderated list focusing on neural-symbolic reasoning, learning and computation, with a broad view of the subject. Neural-symbolic computation is an interdisciplinary research area borrowing from computer science, artificial intelligence, neural computation, machine learning, computational logic, cognitive and neurosciences, psychology and philosophy. Topics of interest include: Network reasoning and inference Reasoning about uncertainty Learning from structured data Statistical relational learning Integrated reasoning and learning Expressive reasoning with robust learning Nonclassical models of computation Computational theories of mind Cognitive computation, abduction and analogy Knowledge extraction from complex networks Deep learning and reasoning Combination of systems Efficient implementations of integrated learning and reasoning Applications in large-scale data analysis problems including simulation and training, robotics, the web, multi-agent systems, fault diagnosis, bioinformatics, argumentation, normative systems, security, multi-modal learning, visual information processing, anomaly detection, fraud prevention. Comments and criticisms of results in the literature, open problems, and research queries are encouraged. Announcements of relevant meetings, publications, and abstracts of papers are also welcome. Artur d'Avila Garcez Department of Computing City University London www.soi.city.ac.uk/~aag To see the collection of prior postings to the list, visit the NeSy Archives. (The current archive is only available to the list members.)
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