As the learning take place, connections are modified considering a defined error. There are several ways to solve the same problem with different weight connections.

In complement to Erik Cuevas' post, one such a solution in a dynamic (evolutive) context may be "Soft Competitive Learning" as suggested by Bernd Fritzke. In particular, "Growing Cell Structures" are derived from concepts like SOM, Neural Gas and Elastic Nets. Follow:

• B. Fritzke, " Growing Cell Structures A Self-Organizing Network for Unsupervised and Supervised Learning ", 1994 - http://www.wi.hs-wismar.de/~cleve/vorl/projects/dm/ss13/SOTA/quellen/1-s2.0-0893608094900914-main.pdf
• B. Fritzke, "Growing Grid - a self-organizing network with constant neighborhood range and adaptation strength", 1995 - https://booksc.org/book/6920674/b62794
• B. Fritzke, " A Growing Neural Gas Network Learns Topologies ", 1995 - https://papers.nips.cc/paper/893-a-growing-neural-gas-network-learns-topologies.pdf
• Doherty et al., " Hierarchical Growing Neural Gas ", 2005 - https://uhra.herts.ac.uk/bitstream/handle/2299/3968/901763.pdf?sequence=1&isAllowed=y
• https://www.demogng.de/JavaPaper/node23.html

and more recently:

• Lopez-Rubio et al., "Growing Hierarchical Probabilistic Self-Organizing Graphs", 2011 -

  Article Growing Hierarchical Probabilistic Self-Organizing Graphs

• Fiser et al., " Growing neural gas efficiently ", 2013 -

  Article Growing neural gas efficiently

Before using ANN, it need a learning which is a process that produces an output that is as close as possible to the desired output by adjusting network parameters , there are two learning methods: Supervised and unsupervised.

Learning rules of ANN includes weights modifiable depending on the input it receives, its output value, and the associated teacher response.

I can't doubt the possibility. Following.

when you start walking you will get problems, So start working first, if start facing difficulties, start learning to solving the challenges one by one . Here before supervising you have to learn yourself absolutely doing that work.

Connex/complementary issue on RG: https://www.researchgate.net/post/Combining_Self_organized_maps_with_Affinity_Propagation_dimension_reduction