For Python, someone else has already mentioned Mesa: https://github.com/projectmesa/mesa/
You can find some more lists at https://www.comses.net/ -- sadly https://en.wikipedia.org/wiki/Comparison_of_agent-based_mode... looks fairly sparse / a little outdated (though I have only passing familiarity with most of those).
Finally, I think a great technical source of theory about these models comes from Cosma Shalizi's notebook on ABM: http://bactra.org/notebooks/agent-based-modeling.html He's one of the single best sources I've seen for describing systems for formally estimating ABMs.
Netlogo is great for fast prototyping, but at least as of ...well a number of years ago now, there was a noticeable lack of scientific computing libraries. For example numerical optimization routines were extremely basic. I had to use a user-contributed package to solve a root finding problem.
Honestly for this type of work I typically write my own from scratch in Python. Here's a great set of lectures and code from Blake LeBaron, "from sratch" in Python, for finance ABMs: http://people.brandeis.edu/~blebaron/classes/agentfin/ ...and here's a nice from scratch Schelling model in Python: https://lectures.quantecon.org/py/schelling.html
StarLogo and NetLogo were some of my first languages. Modeling real-world systems is an immensely powerful educational tool. It helps contextualize programming in a relatable way, and it helps you to learn about complexity and the way the world works at the same time.
I used both of them about 10 years ago when I was in academia in a PostDoc. I taught Agent Based Modelling and Simulation to Social Sciences PhD Students. I also had the opportunity to work with Klaus Troitzsch ( https://en.wikipedia.org/wiki/Klaus_G._Troitzsch).
These kind of models yield really interesting results. But people have to be VERY careful on how to interpret their outcomes, as some people make the mistake to try to take them as direct forecasting. Also, they suffer very much from the garbage-in/garbage-out problem.
http://tinlizzie.org/~ohshima/shadama2/live2017/
A bit tricky due to shader limitations, but very fast. You can use a million particles at a time. This is a product of HARC/VPRI cooperation, from what I understand.