CfP special issue of the Journal of Symbolic Computation JSC on interaction of symbolic computation & machine learning

Symbolic computation (SC) aims at providing algorithmic solutions to problems dealing with symbolic objects such as terms, formulas, programs, representations of algebraic objects, etc. From the beginning, SC was also considered a major approach to "artificial intelligence", since the problems solved by SC, typically, are problems that were considered hard for "human intelligence". Meanwhile, machine learning (ML) methods, developed in parallel to symbolic methods for solving hard "artificial intelligence" problems, achieved spectacular results in numerous applications in recent years. This special issue is dedicated to the interaction of symbolic computation and machine learning methods seen as the two major approaches to "artificial intelligence". We expect dramatic advances from a much closer interaction of the SC and the ML approaches to artificial intelligence.

The special issue is organized as a follow-up of the 24th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing, SYNASC 2022. Participants of the symposium, as well as other authors, are invited to submit contributions. We welcome submissions describing the interaction of SC and ML methods, techniques, and tools, and their applications in AI. This special issue welcomes high-quality contributions, including papers with original research results as well as review articles. They will be peer-reviewed using the standard refereeing procedure of the Journal of Symbolic Computation.