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127 lines
3.4 KiB
127 lines
3.4 KiB
#include "dbc.hpp"
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#include "goap.hpp"
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namespace ai {
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using namespace nlohmann;
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using namespace dbc;
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bool is_subset(State& source, State& target) {
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State result = source & target;
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return result == target;
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}
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void Action::needs(int name, bool val) {
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if(val) {
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$positive_preconds[name] = true;
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$negative_preconds[name] = false;
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} else {
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$negative_preconds[name] = true;
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$positive_preconds[name] = false;
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}
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}
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void Action::effect(int name, bool val) {
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if(val) {
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$positive_effects[name] = true;
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$negative_effects[name] = false;
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} else {
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$negative_effects[name] = true;
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$positive_effects[name] = false;
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}
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}
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bool Action::can_effect(State& state) {
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return ((state & $positive_preconds) == $positive_preconds) &&
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((state & $negative_preconds) == ALL_ZERO);
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}
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State Action::apply_effect(State& state) {
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return (state | $positive_effects) & ~$negative_effects;
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}
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int distance_to_goal(State& from, State& to) {
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auto result = from ^ to;
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return result.count();
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}
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Script reconstruct_path(std::unordered_map<Action, Action>& came_from, Action& current) {
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Script total_path{current};
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int count = 0;
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while(came_from.contains(current) && count++ < 10) {
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current = came_from.at(current);
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if(current != FINAL_ACTION) {
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total_path.push_front(current);
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}
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}
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return total_path;
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}
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inline int h(State& start, State& goal) {
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return distance_to_goal(start, goal);
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}
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inline int d(State& start, State& goal) {
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return distance_to_goal(start, goal);
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}
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ActionState find_lowest(std::unordered_map<ActionState, int>& open_set) {
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check(!open_set.empty(), "open set can't be empty in find_lowest");
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const ActionState *result = nullptr;
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int lowest_score = SCORE_MAX;
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for(auto& kv : open_set) {
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if(kv.second < lowest_score) {
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lowest_score = kv.second;
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result = &kv.first;
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}
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}
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return *result;
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}
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std::optional<Script> plan_actions(std::vector<Action>& actions, State& start, State& goal) {
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std::unordered_map<ActionState, int> open_set;
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std::unordered_map<Action, Action> came_from;
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std::unordered_map<State, int> g_score;
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ActionState start_state{FINAL_ACTION, start};
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g_score[start] = 0;
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open_set[start_state] = g_score[start] + h(start, goal);
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while(!open_set.empty()) {
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auto current = find_lowest(open_set);
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if(is_subset(current.state, goal)) {
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return std::make_optional<Script>(reconstruct_path(came_from, current.action));
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}
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open_set.erase(current);
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for(auto& neighbor_action : actions) {
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// calculate the State being current/neighbor
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if(!neighbor_action.can_effect(current.state)) {
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continue;
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}
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auto neighbor = neighbor_action.apply_effect(current.state);
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int d_score = d(current.state, neighbor);
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int tentative_g_score = g_score[current.state] + d_score;
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int neighbor_g_score = g_score.contains(neighbor) ? g_score[neighbor] : SCORE_MAX;
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if(tentative_g_score < neighbor_g_score) {
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came_from.insert_or_assign(neighbor_action, current.action);
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g_score[neighbor] = tentative_g_score;
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// open_set gets the fScore
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ActionState neighbor_as{neighbor_action, neighbor};
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open_set[neighbor_as] = tentative_g_score + h(neighbor, goal);
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}
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}
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}
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return std::nullopt;
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}
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}
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