The Teeny Tiny Mansion (TTTM) is a mockup text adventure game that is formally
proven to have no "dead ends". I.e. all player actions will result in a state
in which the game is still winnable.
I started thinking about formal verification for adventures games after I
half-jokingly wrote the following tweet, referring to a bug that has been
discussed on the Thimbleweed Park Development Blog:
https://twitter.com/oe1cxw/status/850861311709851650
TTTM is a proof-of-concept showing that formally verified adventure games are
possible, and how they could be built. (Please note that TTTM does not aim to
be a very interesting game. So keep your expectations low.)
I'll first briefly describe why I think formal verification of adventure games
is useful, then describe the TTTM game itself, and then describe how the formal
proof I have implemented works. Finally I'll close with some additional remarks
on how this techniques could be employed in real-world games.
My aim is not only to explain how to to formally verify an adventure game,
but also to sneak in some basic knowledge about formal verification and maybe
get you interested in formal methods in general.
This example uses cbmc as C model checker. The Makefile builds the game and
runs all the formal tests necessary to prove that there are no dead ends in
the game.
Why Formal Verification for Adventure Games?
--------------------------------------------
(Good) Adventure Games are not linear. The player has a choice in what order to
solve puzzles and has certain freedoms in exploring the world. However, to much
freedom can increase the complexity of a game significantly, and make it
impossible for game designers and beta testers to make sure the game cannot get
into a state that the designers did not anticipate. The most extreme example of
this is a situation where the player gets stuck and cannot win the game anymore
(without loading a previously saved state of the game).
Not only can formal verification help finding those problems early in the
design (before beta testing). I believe it would also enable game designers to
create more open games, that would be impossible to audit thoroughly by staring
at a story graph and by employing human beta testers.
This project (TTTM) demonstrates a method that can be used to prove that an
adventure game does not have a reachable state in which the game cannot be
completed.
The Teeny Tiny Mansion
----------------------
TTTM has 2 playable characters (Alice and Bob) and 4 rooms (Red Room, Blue Room,
West Room, and East Room). There are also 3 doors:
+----------------------------+ +----------------------------+
| | | |
| | | |
| | | |
| | | |
| | | |
| Red | | Blue |
| Room | | Room |
| | | |
| | | |
| | | |
| | | |
+-------- ---------+ +--------- --------+
| | | |
| Red Door | | Blue Door |
| | | |
+-------- ---------+ +--------- --------+
| | | |
| | | |
| | | |
| | | |
| |-----------| |
| West Green East |
| Room Door Room |
| |-----------| |
| | | |
| | | |
| | | |
| | | |
+----------------------------+ +----------------------------+
Alice's goal is to go to the Red Room and Bob's goal is to go to the Blue Room.
There are 3 keys in the game: Red Key, Blue Key, and Green Key.
A character can only walk through a door if she/he has the matching key
in her/his inventory. (The doors automatically close behind them when
they walk through.)
Characters can pass keys to each other when they are in the same room.
Initially Alice, Bob, and the three keys are randomly placed in the West Room
and East Room.
When a character reaches her/his destination room then the character will
refuse to leave again.
There are two possible scenarios for dead ends:
1. The random initial position might be unsolvable. For example, both
characters could be placed in the West Room and all keys in the East Room.
2. A character can walk into her or his destination room without providing
the necessary assistance to the other character first.
The game avoids those scenarios (unless compiled with -D BAD_GAME_DESIGN)
by adding the following features:
1. Only solvable initial configurations are created.
2. A character refuses to walk into her/his destination room when the other
character still needs help from this character first to ultimately reach
his/her destination room.
Formal methods are used to confirm that the game with this two additional
features indeed cannot reach an unwinnable state.
My simple game engine
---------------------
For simplicity TTTM (and its formal proofs) are written in plain C99.
The game itself has two major data types:
typedef ... game_state_t;
typedef ... game_action_t;
The function make_initstate() creates a pseudo-random init state for the game:
game_state_t state;
uint32_t initseed = ...;
make_initstate(&state, initseed);
The function query_actions() creates a list of possible actions that the user
can perform in a given state:
game_action_t action_list[MAX_ACTIONS];
int num_actions = query_actions(&state, action_list);
And the function apply_action() applies a given action to a given game state:
int user_input = ...;
apply_action(&state, &action_list[user_input]);
The game simply creates an initial state and then runs a loop that calls
query_actions(), asks the user which action they want to perform, and then
calls apply_action() for the selected action, until the game is won.
Note that nothing in this interface is in any way specific to the TTTM game
itself. Therefore the method for proving the absence of dead ends that I
describe below is generic.
Formally proving the game has no dead ends
------------------------------------------
For the formal proof we need to provide a few additional functions. Note that
the proofs simultaneously prove the correctness of the actual game and those
additional functions. So even though there is additional work required to write
those additional functions, we don't create an additional surface for new bugs
as all bugs in those additional functions would be caught by the formal checks
we perform using them. (Depending on how formal_action_valid() is implemented
there might be an exception to that rule for this function. See also Closing
Thoughts below.)
First we need to define a set of valid states. This is done by creating a
function that evaluates set membership for this set:
bool formal_state_valid(const game_state_t *state);
I.e. this function returns true for all states that are members of the set
of valid states, and false for all other states.
The set of valid states must have the following properties:
- It is an over-approximation of all reachable states. I.e. all states that
are reachable from an initial state must be members of the set.
- All valid states must be "alive", i.e. it must be possible to finish the
game from a valid state.
- The set membership must be an inductive invariant. That means a state
reachable from a valid state via a valid action must also be a valid state.
We also need a function that tells us if a given action is valid in a given
state:
bool formal_action_valid(const game_state_t *state, const game_action_t *action);
In our case this function is trivial: It simply calls query_actions() and checks
if the given action is a member of the list created by query_actions().
Then we need a rather complex function that takes a game state and produces
an action that brings us closer to finishing the game:
void formal_actor(const game_state_t *state, game_action_t *action);
For long games we need an additional function that scores the current game
state. This function is needed if the longest path from any valid state to the
end of the game is too long for the naive implementation of the formal proof
that I describe in the next section:
typedef ... critic_score_t;
critic_score_t formal_critic(const game_state_t *state);
There must also be a transitive less-than operator for those scores that allows
us to measure game progress:
bool lt_scores(critic_score_t score1, critic_score_t score2);
In TTTM critic_score_t is simply int and lt_scores() is implemented as
score1 < score2.
There are a few proofs in tttm.c that together prove that there are no dead
ends in the game. The Makefile runs them all (with cbmc). The proof functions
all have names that start with "prove_". For example, to prove with cbmc that
all initial states are valid states:
cbmc -D FORMAL --function prove_init_validness tttm.c
The following sections describe the individual proofs in more detail.
Proving properties of the set of valid states
---------------------------------------------
First let's check if all initial states are contained in the set of valid
states. The following function implements this proof:
void prove_init_validness(uint32_t seed)
{
game_state_t state;
make_initstate(&state, seed);
assert(formal_state_valid(&state));
}
The formal verification tool effectively runs this function with all possible
seed values and checks if the assert() is violated in any of the cases. But it
uses a more much efficient method to accomplish this than running the function
2^32 (approximately 4 billion) times.
Next we need to prove that formal_state_valid() is an inductive invariant. This
is also relatively simple:
void prove_completeness(game_state_t state, game_action_t action)
{
if (!formal_state_valid(&state))
return;
if (!formal_action_valid(&state, &action))
return;
apply_action(&state, &action);
assert(formal_state_valid(&state));
}
The "if (..) return" statements effectively implement assumptions: We assume that
the given state is valid and that the given action is valid for that state. In all
other cases we simply return early before asserting anything.
For valid state-action pairs we then apply the action to the state and assert
that the new state is also a valid state. If the set of valid states is not an
inductive invariant, then this assert will fail for at least one valid
state-action-pair, and the model checker will find this case for us.
Finally we need to check that formal_actor() only returns valid actions. This
allows us to assume that formal_actor() will always return a valid action in the
more complex proofs below, drastically decreasing the complexity of those proofs.
void prove_actor_validness(game_state_t state)
{
if (!formal_state_valid(&state))
return;
game_action_t action;
formal_actor(&state, &action);
assert(formal_action_valid(&state, &action));
}
Now we have everything in place to actually prove the absence of dead ends in
our game. I describe two methods for doing that in the next two sections.
Proving bounded liveness for the actor function
-----------------------------------------------
It is possible to finish TTTM from any valid state in 18 actions or fewer. Thus
the MAX_FINISH_DEPTH define in tttm.c is set to 18. We have already proven that
all reachable states are contained within our set of valid states. If we can now
prove that formal_actor() can finish the game within 18 actions from any valid
state, then we have proven that the game has no dead ends.
void prove_bounded_liveness(game_state_t state)
{
if (!formal_state_valid(&state))
return;
for (int i = 0; i < MAX_FINISH_DEPTH; i++)
{
game_action_t action;
formal_actor(&state, &action);
// assert(formal_action_valid(&state, &action));
if (action.op == OP_FINISH)
return;
apply_action(&state, &action);
}
assert(0);
}
(The action satisfying "action.op == OP_FINISH" is only valid when the game
is completed.)
Notice the commented-out assert()? We don't need this assert because
prove_actor_validness() has already proven that formal_actor() will always
return a valid action for the given state. Enabling this assert would
drastically increase the complexity of the prove without adding anything
useful to it.
If proving prove_bounded_liveness() succeeds then we are done. However, if it
does not succeed then this can mean any of the following:
- Maybe the game does contain a dead end. Then we have to fix it.
- Maybe the game is OK but the formal_actor() function does not know how to
solve it from a certain state.
- Maybe the game is OK and formal_actor() is OK, but MAX_FINISH_DEPTH is
an insufficient number of actions to solve from any valid state.
When an error is reported by cbmc then it will output the value of the
state argument as part of its report. One can set the CEX_STATE define
to this value, recompile, and run ./tttm to play interactively from that
initial state, or run ./tttm_autorun to let formal_actor() solve from
that initial state. This can be used to narrow down the issue and come
up with a suitable fix.
For large values of MAX_FINISH_DEPTH and complex games this approach will not
yield a proof that can be computed with current C model checkers. In the
following section I describe a slightly more complex method that will also
work with long and complex games.
Proving unbounded liveness for the actor function
-------------------------------------------------
Long games would require large values for MAX_FINISH_DEPTH, exponentially
exploding the search space for the model checker for proving that the game
can be completed from any valid state.
However, we can replace the notion of completing the game within a certain
bound with the notion of making progress within a certain bound.
As long as we can guarantee that formal_actor() can make progress within a
certain bound, and assuming that the game has only a finite number of states,
we can guarantee that formal_actor() will ultimately solve the game.
In order to measure progress we need a formal_critic() function that takes a
(valid) state and returns a metric the measures how far we have come in the
game. In TTTM this metric is simply an integer, but it could be any data
structure as long as a transitive less-than operator to compare two scores is
provided. Transitivity simply means that A < B and B < C implies A < C. Without
transitivity we could go in circles and still make constant "progress". Let's
first prove transitivity for our score compare function:
void prove_transitiveness(game_state_t state1, game_state_t state2, game_state_t state3)
{
if (!formal_state_valid(&state1))
return;
if (!formal_state_valid(&state2))
return;
if (!formal_state_valid(&state3))
return;
critic_score_t score1 = formal_critic(&state1);
critic_score_t score2 = formal_critic(&state2);
critic_score_t score3 = formal_critic(&state3);
if (lt_scores(score1, score2) && lt_scores(score2, score3))
assert(lt_scores(score1, score3));
}
Now lets prove that formal_actor() will always make progress within at most
4 actions (the value of MAX_PROGRESS_DEPTH in tttm.c):
void prove_unbounded_liveness(game_state_t state)
{
if (!formal_state_valid(&state))
return;
critic_score_t old_score = formal_critic(&state);
for (int i = 0; i < MAX_PROGRESS_DEPTH; i++)
{
game_action_t action;
formal_actor(&state, &action);
// assert(formal_action_valid(&state, &action));
if (action.op == OP_FINISH)
return;
apply_action(&state, &action);
}
critic_score_t new_score = formal_critic(&state);
assert(lt_scores(old_score, new_score));
}
On my machine and with cbmc, TTTM can be proven to be free of dead ends within
15 seconds using the bounded method implemented in prove_bounded_liveness(),
and within 2 seconds using prove_unbounded_liveness(). The more complex
unbounded method would not have been absolutely necessary to prove TTTM, but
for longer games that cannot be solved in a small number of actions, the
bounded approach becomes infeasible and only unbounded checks are of any
practical interest.
Additional Remarks on Actors and Critics
----------------------------------------
There is no need for formal_actor() and formal_critic() to be independent
functions. In most cases it would probably be much easier to create one single
function that returns the next action and also a score for the current state.
In TTTM the actor and critic functions are ad-hoc implementations for this very
simple game. For more complex games a more structured approach would be needed.
I will outline such an approach in the following paragraphs.
Lets assume an adventure game with multiple playable characters. Each puzzle
requires a certain set of characters to be in the right locations each while
holding the right items in their inventory. Then they need to execute a
sequence of actions that solves the puzzle. Completion of a puzzle unlocks
more puzzles, i.e. a puzzle can be in one of the following three states: locked,
unlocked, or completed.
The actor for such a game would consist of two main parts: 1. some code that
looks at the game state and decides which puzzle to solve right now, and 2. some
code that determines the next action to solve the current puzzle.
The first part would simply determine which puzzles are in the unlocked state
and then chooses one using a pre-determined list of priorities. Note that the
unlocked state of a puzzle does not need to be explicitly expressed in the game
state. It could also be simply implied by other things, such as the inventory
items the characters have acquired so far.
A function that simply counts the number of solved puzzles can be used to
generate the MSB bits of the critic score. The remaining LSB bits of the score
can then be used to keep track of progress within the current puzzle.
Notice that some "puzzles" in this sense can be rather trivial, like for
example just going to a place and picking up an object.
So the combined actor-critic could look something like this:
critic_score_t formal_actor_critic(const game_state_t *state, game_action_t *action)
{
puzzle_enum_t current_puzzle = determine_current_puzzle(state);
critic_score_t num_solved_puzzles = count_solved_puzzles(state);
critic_score_t current_task_score = 0;
// default for when no action is found
action = INVALID_ACTION;
if (current_puzzle == PUZZLE_A) {
...
}
if (current_puzzle == PUZZLE_B) {
...
}
return (num_solved_puzzles << TASK_SCORE_BITS) | (current_task_score);
}
For the kind of puzzle described above, solving the puzzle can be broken down
in four phases:
1. Bringing the character to a meeting point where they can exchange objects.
2. Exchanging objects.
3. Bringing the characters to the places they need to be to solve the puzzle.
4. Executing the sequence of puzzle-specific actions required to solve the puzzle.
The first three phases can be summarized as setting up to solve the puzzle and
only differ in the set of characters, objects and locations involved. It should
be fairly simply to generalize this part and re-use the same code for all the
puzzles.
The code in formal_actor_critic() for solving a puzzle could look something
like this (the prefix "pa_" is used for functions specific to solving puzzle A):
if (current_puzzle == PUZZLE_A)
{
if (!pa_everyone_has_right_object(state))
{
// We are in phase 1 or 2
if (!pa_everyone_is_at_meeting_place(state))
{
// We are in phase 1
current_task_score = 1 << PHASE_SCORE_BITS;
current_task_score -= pa_sum_of_distance_to_meeting_place(state);
action = pa_move_to_meeting_action(state);
}
else
{
// We are in phase 2
current_task_score = 2 << PHASE_SCORE_BITS;
current_task_score -= pa_sum_of_object_in_wrong_inventory(state);
action = pa_exchange_inventory_items_action(state);
}
}
else
{
// We are in phase 3 or 4
if (!pa_everyone_is_in_place(state))
{
// We are in phase 3
current_task_score = 3 << PHASE_SCORE_BITS;
current_task_score -= pa_sum_of_distance_to_puzzle_places(state);
action = pa_move_to_puzzle_action(state);
}
else
{
// We are in phase 4
current_task_score = 4 << PHASE_SCORE_BITS;
current_task_score += pa_puzzle_steps_performed(state);
action = pa_puzzle_step_action(state);
}
}
}
The main challenge here is of course that formal_actor_critic() has no
additional state that it can use to do things like remembering which puzzle it
is trying to solve. It has to infer the next action by only looking at the game
state.
I am, however, confident that the general scheme that I described above can be
used to write actor-critic functions for even complex adventure games.
Discussion
----------
There is an argument to be had for a solution that directly proves if a given
state is solvable, without the need for an explicit actor and critic function
(or even without the need for formal_state_valid). Techniques that would enable
this certainly exist in the formal verification research, but I don't know if
any of it is implemented in existing open source C/C++ model checkers.
However, it would certainly drastically increase the overall complexity of the
proof in a way that renders the use of such methods impractical for large and
complex games. Furthermore I would argue that a proof using explicit functions
provided by the game design team is more valuable:
Consider a situation where there is a bug that would prevent a player from
finishing the game using normal play, but there is also an obscure work-around
that most users would never find. An automatic prover would not be able to
distinguish the obscure work-around from regular game play and thus would
incorrectly claim that the game is bug-free. Having an explicit actor function
makes sure that not only the game always stays winnable, it also makes sure
that the game is always winnable the intended way.
Here is a concrete (made up) example:
Consider a situation where in order to unlock a new puzzle a cut scene must be
activated. Say the cut scene plays in the kitchen. But for some reason the
player decided that the kitchen is a good place to park the characters she is
not using right now. The game meanwhile is waiting with playing the cut scene
until the kitchen is vacated. The game designers might have thought that a
certain puzzle would force the player to move all characters to a place that is
not the kitchen. But maybe the player was able to do that puzzle before the
cut scene became available. An automatic prover might simply design it's
auto-generated actor so that it moves all characters out of the kitchen to
activate the cut-scene. But a human programmer working on the actor code would
quickly realize that the "move everyone out of the kitchen puzzle" is a boring
puzzle, and that instead the prerequisites for the puzzle that was designed to
force the player to leave the kitchen must be fixed. When this is done then the
actor does not need to know anything about triggering that cut scene, because
it is now guaranteed that the cut scene will play as a side effect of a real
puzzle. Instead of adding anything to the actor, something like the following
assertion would need to be added to formal_state_valid():
if (puzzle_42_is_solved(state) && !cut_scene_23_has_played(state))
return false;
The roles of formal_actor() and formal_critic(), formal_state_valid(), and
formal_action_valid() can be summarized as follows:
formal_action_valid() is a description of what the game explicitly allows the
user to do.
formal_state_valid() is a description of the reachable state space (or an
over-approximation thereof), as implied by formal_action_valid(). This function
can become very large and complex, but that is okay.
formal_actor() and formal_critic() represents what the player must learn about
the world in order to win the game. If there is something really odd that the
actor function must do (such as explicitly vacating the kitchen to trigger a cut
scene), this means that at least in some cases there will be a burden on the
player to do the same odd thing in order to make progress in the game.
Closing Thoughts
----------------
In order to formally prove any real-world adventure games, one would likely
need to build an engine with formal verification in mind. A clear separation of
the high-level game logic (inventory, possible actions in a state, etc) and the
presentation to the player is required, so that the high-level game logic can
be compiled independently of the actual GUI and verified stand-alone.
The GUI would need to create instances of game_action_t and use the same
apply_action() action function as used in the formal proof to modify the
game_state_t struct. (Otherwise we would verify and ship two different games.)
The game must be designed in a way so that game_action_t is sufficiently coarse
to ensure that only a relatively small number of actions is required to solve
the game. Otherwise it would become impractical to formally verify the game.
The biggest challenge probably is to make sure that formal_action_valid()
correctly identifies exactly the set of actions that can be generated using the
GUI. Either a set of additional auxiliary proofs is needed to ensure that this
is the case, or the game must have a way of enumerating the possible actions
and formal_action_valid() could just use that feature (this is what I did for
proving TTTM).
Proving that a game is free of dead ends is only one property of an adventure
game that can be formally verified using this technique. Another application
would be to prove that certain pairs of events in the game always happen in
the right order, guaranteeing that the story always makes sense independent
of the sequence of actions the player chooses.
I hope you found this quick exploration of formal verification of adventure
games interesting. If you want to experiment with formal methods yourself I'd
recommend you download CBMC or ESBMC and give it a try in your own projects.
(ESBMC is based on CBMC, so they are very similar.)
http://www.cprover.org/cbmc/
http://www.esbmc.org/
I myself am working on tools for formal verification of digital hardware. You
can find more information about those projects here:
http://www.clifford.at/papers/2017/smtbmc-sby/
http://symbiyosys.readthedocs.io/
The blog post that inspired me to think about formal verification of adventure
games is "Patch Notes" from April 4th from the Thimbleweed Park Development Blog:
https://blog.thimbleweedpark.com/patch_notes
This README and the C code for TTTM can be found here:
http://svn.clifford.at/handicraft/2017/tttm/
Happy Hacking.
Appendix: References to prior art and similar projects
------------------------------------------------------
Formal Verification of Selected Game-Logic Specifications; Stefan Radomski and Tim Neubacher
http://scxmlworkshop.de/eics2015/submissions/Formal%20Verification%20of%20Selected%20Game-Logic%20Specifications.pdf
Model-checking for adventure videogames; Pablo Moreno-Ger, Rubén Fuentes-Fernández, José-Luis Sierra-Rodríguez, Baltasar Fernández-Manjón
http://www.e-ucm.es/drafts/e-UCM_draft_106.pdf
PuzzleGraph; Rune Skovbo Johansen
https://runevision.itch.io/puzzlegraph
Contact me at @oe1cxw if you have additional references to prior art that I should add here.