There is a ferryman, goat, cabbage and a wolf on one side of a river. The ferryman can cross a river with at most one passenger in his boat. There is a behavioural conflict between
- the goat and the cabbage; and
- the goat and the wolf;
if they are on the same side of the river bank but the ferryman crosses the river or stays on the other bank.
Can ferryman transport all goods to the other side, without any conflicts occuring?
This is a planning problem but can be solved using model checking.
We describe a transition system in which the states represent which goods are at which side of the river. Then we ask if the goal state is reachable from the initial state: Is there a path from the initial state such that it has a state along it at which all the goods are on the other side, and during the transitions to that state the goods are never left in an unsafe, conflicting situation?
We model all possible behaviour (including that which results in conflicts)
as a NuSMV program. The location of each agent is modelled
as a boolean variable: FALSE
denotes that the agent is on the initial bank, and
TRUE
the destination bank. Thus, ferryman = FALSE
means that the ferryman is
on the initial bank, ferryman = TRUE
that he is on the destination bank, and
similarly for the variables goat
, cabbage
and wolf
.
The variable carry takes a value indicating whether the goat, cabbage,
wolf or nothing is carried by the ferryman. The definition of next(carry)
works as follows. It is non-deterministic, but the set from which a value is
non-deterministically chosen is determined by the values of ferryman, goat, etc., and always includes FALSE
. If ferryman = goat
(i.e., they are on the same
side) then g
is a member of the set from which next(carry)
is chosen. The
situation for cabbage and wolf is similar. Thus, if ferryman = goat = wolf != cabbage
then that set is {g, w, 0}
. The next value assigned to ferryman
is
non-deterministic: he can choose to cross or not to cross the river. But the
next values of goat
, cabbage
and wolf
are deterministic, since whether they
are carried or not is determined by the ferryman’s choice, represented by the
non-deterministic assignment to carry
; these values follow the same pattern.
./nusmv.exe ferryman.smv
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*** This version of NuSMV is linked to the CUDD library version 2.4.1
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*** This version of NuSMV is linked to the MiniSat SAT solver.
*** See http://minisat.se/MiniSat.html
*** Copyright (c) 2003-2006, Niklas Een, Niklas Sorensson
*** Copyright (c) 2007-2010, Niklas Sorensson
-- specification !(((goat = cabbage | goat = wolf) -> goat = ferryman) U (((cabbage & goat) & wolf) & ferryman)) is false
-- as demonstrated by the following execution sequence
Trace Description: LTL Counterexample
Trace Type: Counterexample
-- Loop starts here
-> State: 1.1 <-
ferryman = FALSE
goat = FALSE
cabbage = FALSE
wolf = FALSE
carry = none
-> State: 1.2 <-
ferryman = TRUE
goat = TRUE
carry = g
-> State: 1.3 <-
ferryman = FALSE
carry = none
-> State: 1.4 <-
ferryman = TRUE
wolf = TRUE
carry = w
-> State: 1.5 <-
ferryman = FALSE
goat = FALSE
carry = g
-> State: 1.6 <-
ferryman = TRUE
cabbage = TRUE
carry = c
-> State: 1.7 <-
ferryman = FALSE
carry = none
-> State: 1.8 <-
ferryman = TRUE
goat = TRUE
carry = g
-> State: 1.9 <-
ferryman = FALSE
wolf = FALSE
carry = w
-> State: 1.10 <-
ferryman = TRUE
carry = none
-> State: 1.11 <-
ferryman = FALSE
cabbage = FALSE
carry = c
-> State: 1.12 <-
ferryman = TRUE
carry = none
-> State: 1.13 <-
ferryman = FALSE
goat = FALSE
carry = g
-> State: 1.14 <-
ferryman = TRUE
carry = none
-> State: 1.15 <-
ferryman = FALSE
Invoking bounded model checking will produce the shortest possible path to violate the property.
Michael Huth and Mark Ryan. 2004. Logic in Computer Science: Modelling and Reasoning about Systems.
Cambridge University Press, USA.