Behavior_Machine
Copyright - Transportation, Bots, and Disability Lab, Carnegie Mellon University
Released under MIT License
This is an implementation of a hierarchical state machine but with additional behavior-tree like features (Sequential, Parallal, etc). Unlike behavior trees, the execution of each state is independent of the tick (A repeative signal generated from the root). The transition of the state are determined by the machine's tick but can be set at different levels
Illustrative Example:
from behavior_machine.core import State, Machine
from behavior_machine.library import PrintState, SequentialState, IdleState
ps1 = PrintState("ps1", "Hello World 1")
ps2 = PrintState("ps2", "Hello World 2")
is1 = IdleState("is1")
ps3 = PrintState("ps3", "Hello World 3")
ss = SequentialState("ss", children=[ps1, ps2])
ss.add_transition_on_success(ps3)
m1 = Machine("m1", ss, rate=10)
m1.add_transition(lambda state, board: state._curr_state._name == "ps3", is1)
m2 = Machine("m2", m1, end_state_ids=['is1'], rate=10)
m2.run()
Documentation
You can view more detailed documentation by following this link
1 maintainer
Release files for behavior-machine 0.4.0
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| behavior_machine-0.4.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 53.1 kB
Release files / behavior_machine-0.4.0.tar.gz
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