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

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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