Forthcoming 5G is envisioned to provide services to a diverse set of verticals with varying performance and QoS (Quality of Service) requirements. Network slicing is one of the key enabling technologies that allows this heterogeneous service delivery by running multiple virtual networks with different network characteristics on a common physical infrastructure. Naturally, various 5G use cases related to network slicing such as resource allocation, placement, and pricing of network slices have emerged. One of the crucial challenges is to model and simulate these use cases and test/train decision-making algorithms in a realistic environment before deployment in production. We tackle this problem by proposing an agent-based framework to model and simulate end-to-end 5G networks as well as implement its use cases. Furthermore, we demonstrate the capability of our simulator to integrate decision-making approaches by presenting algorithms implemented on our simulation environment for placing and pricing network slices.