<｜begin▁of▁sentence｜>### Instruction:
As a project scheduler, let's consider you're mapping out the dependencies between project milestones in a schedule, which can be visualized as a directed acyclic graph. The current dependencies are outlined as follows: Milestone 1 must be completed before both Milestone 2 and Milestone 3 can commence. Furthermore, both Milestones 2 and 3 need to be completed prior to starting Milestone 4.

Now, in order to optimize the resource allocation and identify the sets of milestones that can be worked on concurrently without any interdependencies, you're looking to determine all the possible antichains within this project's milestone graph.

Can you use NetworkX to enumerate all the antichains from the project's milestone dependency DAG, as defined by the edges [(1, 2), (1, 3), (2, 4), (3, 4)]? This would help in better understanding the scheduling flexibility you have with the resources at your disposal.
### Response:
import networkx as nx

# Create a directed acyclic graph (DAG)
DG = nx.DiGraph([(1, 2), (1, 3), (2, 4), (3, 4)])

# Generate antichains
antichains_list = list(nx.antichains(DG))

print('Antichains:', antichains_list)
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