Now have the ability to do partial solutions that will create potential paths to the goal, and a test that runs the scripts from plans in different scenarios. Also, this ai_debug thing needs some work.

goap.cpp

@@ -1,5 +1,6 @@
 #include "dbc.hpp"
 #include "goap.hpp"
+#include "ai_debug.hpp"
 
 namespace ai {
   using namespace nlohmann;
@@ -82,21 +83,21 @@ namespace ai {
     return *result;
   }
 
-  std::optional<Script> plan_actions(std::vector<Action>& actions, State& start, State& goal) {
+  ActionPlan plan_actions(std::vector<Action>& actions, State start, State goal) {
     std::unordered_map<ActionState, int> open_set;
     std::unordered_map<Action, Action> came_from;
     std::unordered_map<State, int> g_score;
-
-    ActionState start_state{FINAL_ACTION, start};
+    ActionState current{FINAL_ACTION, start};
 
     g_score[start] = 0;
-    open_set[start_state] = g_score[start] + h(start, goal);
+    open_set[current] = g_score[start] + h(start, goal);
 
     while(!open_set.empty()) {
-      auto current = find_lowest(open_set);
+      current = find_lowest(open_set);
 
       if(is_subset(current.state, goal)) {
-        return std::make_optional<Script>(reconstruct_path(came_from, current.action));
+        return {true,
+          reconstruct_path(came_from, current.action)};
       }
 
       open_set.erase(current);
@@ -122,6 +123,6 @@ namespace ai {
       }
     }
 
-    return std::nullopt;
+    return {false, reconstruct_path(came_from, current.action)};
   }
 }