$BENCH_HOME/bin/storm-pomdp --prism $BENCH_HOME/models/clean/clean.prism --prop $BENCH_HOME/models/clean/clean.props rbrmax2 -const N=6,B1=90,B2=5 --timemem --statistics --revised --reward-aware 1,0 --belief-exploration discretize --resolution 12 --triangulationmode static
Storm-pomdp. Sequential approach, cost aware, with discretization and resolution 12
Storm-POMDP 1.9.1 (dev)
Date: Mon Feb 10 10:10:19 2025
Command line arguments: --prism $BENCH_HOME/models/clean/clean.prism --prop $BENCH_HOME/models/clean/clean.props rbrmax2 -const 'N=6,B1=90,B2=5' --timemem --statistics --revised --reward-aware '1,0' --belief-exploration discretize --resolution 12 --triangulationmode static
Current working directory: $BENCH_HOME/experiments64gb
Time for model input parsing: 0.002s.
Time for model construction: 0.012s.
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Model type: POMDP (sparse)
States: 37
Transitions: 74
Choices: 50
Observations: 2
Reward Models: energy, clean
State Labels: 3 labels
* deadlock -> 0 item(s)
* init -> 1 item(s)
* goal -> 1 item(s)
Choice Labels: 3 labels
* clean -> 13 item(s)
* move -> 13 item(s)
* consume -> 24 item(s)
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Analyzing property 'Pmax=? [true U^{rew{"energy"}<=90 , rew{"clean"}>5 }"goal"]'
Perform unfolding for observation levels.
bounded reachability processing done. POMDP Information:
--------------------------------------------------------------
Model type: POMDP (sparse)
States: 203
Transitions: 553
Choices: 322
Observations: 7
Reward Models: dim0_levelReward
State Labels: 4 labels
* goal -> 14 item(s)
* dim1_active -> 2 item(s)
* deadlock -> 0 item(s)
* init -> 1 item(s)
Choice Labels: 3 labels
* move -> 119 item(s)
* consume -> 84 item(s)
* clean -> 119 item(s)
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Transformed formula: Pmax=? [true Urew{"dim0_levelReward"}<=90 ("goal" & "dim1_active")]
Time for pre-processing: 0.000s.
Exploring the belief MDP...
Exploring the belief space...
Constructing the belief MDP...
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Model type: MDP (sparse)
States: 1428
Transitions: 3780
Choices: 2480
Reward Models: dim0_levelReward
State Labels: 3 labels
* target -> 2 item(s)
* init -> 1 item(s)
* bottom -> 1 item(s)
Choice Labels: none
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Analyzing property 'Pmax=? [true Urew{"dim0_levelReward"}<=90 "target"]' on the belief MDP...
Transformation of transition rewards resulted in a model with 2390 states. 1.673669468 times more states than the original belief MDP.
Merging of sink states resulted in a model with 931 states.
Epoch model for epoch <_> is cyclic.
---------------------------------
Statistics:
---------------------------------
#checked epochs: 92.
overall Time: 0.003s.
Epoch Model building Time: 0.001s.
Epoch Model checking Time: 0.001s.
---------------------------------
Time for exploring beliefs: 0.003s.
Time for building the belief MDP: 0.000s.
Time for analyzing the belief MDP: 0.005s.
##### POMDP Approximation Statistics ######
# Input model:
--------------------------------------------------------------
Model type: POMDP (sparse)
States: 203
Transitions: 553
Choices: 322
Observations: 9
Reward Models: dim0_levelReward
State Labels: 4 labels
* goal -> 14 item(s)
* dim1_active -> 2 item(s)
* deadlock -> 0 item(s)
* init -> 1 item(s)
Choice Labels: 3 labels
* move -> 119 item(s)
* consume -> 84 item(s)
* clean -> 119 item(s)
--------------------------------------------------------------
# Max. Number of states with same observation: 84
# Total check time: 0.009s
##########################################
Result: ≤ 0.9999999111
Time for POMDP analysis: 0.009s.
Performance statistics:
* peak memory usage: 51MB
* CPU time: 0.022s
* wallclock time: 0.036s
############################## Notes ##############################
Storm-pomdp. Sequential approach, cost aware, with discretization and resolution 12