$BENCH_HOME/bin/storm-pomdp --prism $BENCH_HOME/models/clean/clean.prism --prop $BENCH_HOME/models/clean/clean.props rbrmax2 -const N=6,B1=60,B2=5 --timemem --statistics --revised --reward-aware 30,0 --belief-exploration discretize --resolution 10 --triangulationmode static
Storm-pomdp. Sequential approach, cost aware, with discretization and resolution 10
Storm-POMDP 1.9.1 (dev)
Date: Mon Feb 10 14:16:07 2025
Command line arguments: --prism $BENCH_HOME/models/clean/clean.prism --prop $BENCH_HOME/models/clean/clean.props rbrmax2 -const 'N=6,B1=60,B2=5' --timemem --statistics --revised --reward-aware '30,0' --belief-exploration discretize --resolution 10 --triangulationmode static
Current working directory: $BENCH_HOME/experiments64gb
Time for model input parsing: 0.001s.
Time for model construction: 0.007s.
--------------------------------------------------------------
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)
--------------------------------------------------------------
Analyzing property 'Pmax=? [true U^{rew{"energy"}<=60 , rew{"clean"}>5 }"goal"]'
Perform unfolding for observation levels.
bounded reachability processing done. POMDP Information:
--------------------------------------------------------------
Model type: POMDP (sparse)
States: 2158
Transitions: 4427
Choices: 3056
Observations: 5
Reward Models: dim0_levelReward
State Labels: 4 labels
* goal -> 217 item(s)
* dim1_active -> 31 item(s)
* deadlock -> 0 item(s)
* init -> 1 item(s)
Choice Labels: 3 labels
* move -> 898 item(s)
* consume -> 1260 item(s)
* clean -> 898 item(s)
--------------------------------------------------------------
Transformed formula: Pmax=? [true Urew{"dim0_levelReward"}<=2 ("goal" & "dim1_active")]
Time for pre-processing: 0.001s.
Exploring the belief MDP...
Exploring the belief space...
############################## Notes ##############################
Storm-pomdp. Sequential approach, cost aware, with discretization and resolution 10