public bool contains(Move move, Percept percept)
{
if (perception_data[move] == percept)
{
return(true);
}
return(false);
}
public PerceptionState()
{
perception_data = new SortedDictionary <Move, Percept>();
foreach (var i in Move.get_moves())
{
perception_data.Add(i, Percept.initialized());
}
set_name();
}
private readonly static List <Percept> list; //for counting
//This might not be necessary
static Percept()
{
wall_percept = new Percept("Wall");
empty_percept = new Percept("Empty");
can_percept = new Percept("Can");
list = new List <Percept>();
list.Add(wall_percept);
list.Add(empty_percept);
list.Add(can_percept);
initialized_percept = new Percept("initialized");
}
static public void small_dropdown_changed(ComboBox changed_dropdown)
{
if (changed_dropdown.SelectedText != "None.")
{
PerceptionState to_set = new PerceptionState();
Move percept_move = null;
foreach (var i in Move.list)
{
if (changed_dropdown == list_qmatrix_comboboxes[i])
{
percept_move = i;
}
}
//get the percept of the dropdown
Percept keep_for_best_fit = (Percept)changed_dropdown.SelectedItem;
//Build a perception state that matches the dropdowns
foreach (var i in Move.list)
{
to_set.perception_data[i] = (Percept)list_qmatrix_comboboxes[i].SelectedItem;
}
to_set.set_name();
to_set = PerceptionState.list_of_states[to_set]; //Convert to static instance
//This state may not exist in our q-matrix states, because we only changed one of the dropdowns.
//The best solution i think is to make the other dropdowns find the most accurate state.
//Compare all the states in the q-matrix, and display any that is tied for best matched.
//Also, the matching state must have the same item as the dropdown we just changed.
int compare_value = 0;
int temp = 0;
PerceptionState best_perceptionstate = null;
foreach (PerceptionState i in qmatrix_state_combobox_large.Items)
{
temp = to_set.compare(i);
if (temp > compare_value && i.contains(percept_move, keep_for_best_fit))
{
best_perceptionstate = i;
compare_value = temp;
}
}
ViewQmatrixConfiguration(best_perceptionstate);
}
}
static PerceptionState()
{
//Create all 243 possible configurations
list_of_states = new Dictionary <PerceptionState, PerceptionState>();
PerceptionState to_build;
foreach (var i in Percept.get_list())
{
foreach (var j in Percept.get_list())
{
foreach (var k in Percept.get_list())
{
foreach (var l in Percept.get_list())
{
foreach (var m in Percept.get_list())
{
to_build = new PerceptionState();
to_build.perception_data[Move.left()] = i;
to_build.perception_data[Move.right()] = j;
to_build.perception_data[Move.down()] = k;
to_build.perception_data[Move.up()] = l;
to_build.perception_data[Move.grab()] = m;
to_build.set_id(list_of_states.Count);
to_build.set_name();
list_of_states.Add(to_build, to_build);
//list_of_states[to_build] = to_build;
//Add the perception state to our dictionary at a location reachable if we can build a similar dictionary.
}
}
}
}
}
}
//Used when the robot moves *only*, otherwise, the perception will be checked from the state of the unit.
//Generates percepts, and not MoveResults.
public Percept percieve(Move move_to_check)
{
BaseSquare bender_location = board_data[bender.x_coordinate][bender.y_coordinate];
if (move_to_check != Move.grab() && ((BoardSquare)bender_location).check_if_walls_prevent_move(move_to_check))
{
return(Percept.wall()); //Wall percieved
}
else
{
int percieve_x = bender.x_coordinate + move_to_check.grid_adjustment[0];
int percieve_y = bender.y_coordinate + move_to_check.grid_adjustment[1];
BaseSquare percieve_location = board_data[percieve_x][percieve_y];
if (percieve_location.beer_can_present)
{
return(Percept.can());
}
else
{
return(Percept.empty());
}
}
}
