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"# End component elimination\n",
"End Components (ECs) are sets of states in an MDP where:\n",
"* Every state can reach every other state. (Strongly Connected Component)\n",
"* All actions always lead to a state that is also in the MEC (there is no escape)\n",
"\n",
"For analysis, it is often useful to eliminate these MECs to a single state. We will show how to do this using stormpy and stormvogel."
]
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"source": [
"from stormvogel import *\n",
"\n",
"init = pgc.State(x=[\"init\"])\n",
"\n",
"def available_actions(s: pgc.State):\n",
" if \"init\" in s.x:\n",
" return [pgc.Action([\"one\"]), pgc.Action([\"two\"])]\n",
" elif \"mec1\" in s.x or \"mec2\" in s.x:\n",
" return [pgc.Action([\"one\"]), pgc.Action([\"two\"])]\n",
" return [pgc.Action([])]\n",
"\n",
"def delta(s: pgc.State, a: pgc.Action):\n",
" if \"init\" in s.x and \"one\" in a.labels:\n",
" return [(0.5, pgc.State(x=[\"mec1\"])), (0.5, pgc.State(x=[\"mec2\"]))]\n",
" elif \"mec1\" in s.x:\n",
" return [(1, pgc.State(x=[\"mec2\"]))]\n",
" elif \"mec2\" in s.x:\n",
" return [(1, pgc.State(x=[\"mec1\"]))]\n",
" elif \"init\" in s.x and \"two\" in a.labels:\n",
" return [(1, pgc.State(x=[\"mec1\"]))]\n",
" return [(1,s)]\n",
"\n",
"labels = lambda s: s.x\n",
"\n",
"mdp = pgc.build_pgc(\n",
" delta=delta,\n",
" initial_state_pgc=init,\n",
" available_actions=available_actions,\n",
" labels=labels,\n",
" modeltype=ModelType.MDP,)\n",
"vis = show(mdp, layout=Layout(\"layouts/mec.json\"))"
]
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"source": [
"First, let's show the maximal end components of this model."
]
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"[(frozenset({1, 2}), frozenset({(2, Action(labels=frozenset({'two'}))), (1, Action(labels=frozenset({'one'}))), (1, Action(labels=frozenset({'two'}))), (2, Action(labels=frozenset({'one'})))}))]\n"
]
}
],
"source": [
"def stormvogel_get_maximal_end_components(sv_model):\n",
" sp_model = stormpy_utils.mapping.stormvogel_to_stormpy(sv_model)\n",
" f = extensions.choice_mapping(sv_model, sp_model)\n",
" decomposition = stormpy.get_maximal_end_components(sp_model)\n",
" res = []\n",
" for mec in decomposition:\n",
" states = set()\n",
" actions = set()\n",
" for s_id, choices in mec:\n",
" states.add(s_id)\n",
" actions = actions | set(map(lambda x: f.inverse[x], choices))\n",
" res.append((frozenset(states), frozenset(actions)))\n",
" return res\n",
"\n",
"decomp = stormvogel_get_maximal_end_components(mdp)\n",
"print(decomp)"
]
},
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"outputs": [],
"source": [
"vis.highlight_decomposition(decomp)"
]
},
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"cell_type": "markdown",
"id": "66cbaa0a-1165-48c9-8529-1aa2c967defc",
"metadata": {},
"source": [
"Now we perform end component elimination by converting to stormpy and back."
]
},
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"id": "84392fb7-ab3c-4d28-993f-bebe4f72a179",
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"source": [
"import stormpy\n",
"\n",
"def map_state_labels(m, res):\n",
" \"\"\"Based on the result of EC elimination, create a new state labeling that can be used for a new model that captures the result.\n",
" Args:\n",
" m: stormpy model\n",
" res (EndComponentEliminatorReturnTypeDouble): EC result\n",
" \"\"\"\n",
" old_nr_columns = m.transition_matrix.nr_columns\n",
" new_nr_columns = res.matrix.nr_columns\n",
" sl = stormpy.StateLabeling(new_nr_columns)\n",
"\n",
" for s_old in range(old_nr_columns):\n",
" s_new = res.old_to_new_state_mapping[s_old]\n",
" for l in m.labeling.get_labels_of_state(s_old):\n",
" sl.add_label(l)\n",
" sl.add_label_to_state(l, s_new)\n",
" return sl\n",
"\n",
"def map_choice_labels(m_old, m_new, res):\n",
" \"\"\"Based on the result of EC elimination, create a new choice labeling that can be used for a new model that captures the result.\n",
" Args:\n",
" m_old: old stormpy model\n",
" m_new: new strompy model that is based on res\n",
" res (EndComponentEliminatorReturnTypeDouble): EC result\n",
" \"\"\"\n",
" new_nr_rows = m_new.transition_matrix.nr_rows\n",
" cl = stormpy.storage.ChoiceLabeling(new_nr_rows)\n",
" old_nr_columns = m_old.transition_matrix.nr_columns\n",
"\n",
" for s_old in range(old_nr_columns):\n",
" s_new = res.old_to_new_state_mapping[s_old]\n",
" old_no_choices = m_old.get_nr_available_actions(s_old)\n",
" new_no_choices = m_new.get_nr_available_actions(s_new)\n",
" if (old_no_choices == new_no_choices):\n",
" for action_no in range(old_no_choices):\n",
" old_index = m_old.get_choice_index(s_old, action_no)\n",
" labels = m_old.choice_labeling.get_labels_of_choice(old_index)\n",
" new_index = m_new.get_choice_index(s_new, action_no)\n",
" for l in labels:\n",
" cl.add_label(l)\n",
" cl.add_label_to_choice(l, new_index)\n",
" return cl\n",
"\n",
"def simple_ec_elimination(m):\n",
" \"\"\"Perform EC elimination on a stormpy model while preserving labels. \n",
" Label sets of merged states are unified. \n",
" Action labels are preserved when possible.\n",
" Args:\n",
" m: stormpy model\n",
" \"\"\"\n",
" # Keep all states, and consider ecs to be possible anywhere in the model\n",
" subsystem = stormpy.BitVector(m.nr_states, True)\n",
" possible_ec_rows = stormpy.BitVector(m.nr_choices, True)\n",
" res = stormpy.eliminate_ECs(\n",
" matrix = m.transition_matrix, \n",
" subsystem = subsystem,\n",
" possible_ecs = possible_ec_rows,\n",
" add_sink_row_states = subsystem,\n",
" add_self_loop_at_sink_states=True\n",
" )\n",
" new_labels = map_state_labels(m, res)\n",
" components = stormpy.SparseModelComponents(transition_matrix=res.matrix, state_labeling=new_labels)\n",
" m_new = stormpy.storage.SparseMdp(components)\n",
" components.choice_labeling = map_choice_labels(m, m_new, res)\n",
" m_updated = stormpy.storage.SparseMdp(components)\n",
" return m_updated"
]
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