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76 lines
1.9 KiB
76 lines
1.9 KiB
#pragma once
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#include <vector>
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#include "matrix.hpp"
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#include <bitset>
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#include <limits>
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#include <optional>
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#include <nlohmann/json.hpp>
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namespace ailol {
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constexpr const int SCORE_MAX = std::numeric_limits<int>::max();
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constexpr const size_t STATE_MAX = 32;
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using GOAPState = std::bitset<STATE_MAX>;
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const GOAPState ALL_ZERO;
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const GOAPState ALL_ONES = ~ALL_ZERO;
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struct Action {
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std::string $name;
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int $cost = 0;
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GOAPState $positive_preconds;
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GOAPState $negative_preconds;
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GOAPState $positive_effects;
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GOAPState $negative_effects;
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Action(std::string name, int cost) :
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$name(name), $cost(cost) { }
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void needs(int name, bool val);
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void effect(int name, bool val);
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void load(nlohmann::json &profile, nlohmann::json& config);
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bool can_effect(GOAPState& state);
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GOAPState apply_effect(GOAPState& state);
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bool operator==(const Action& other) const {
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return other.$name == $name;
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}
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};
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using AStarPath = std::deque<Action>;
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const Action FINAL_ACTION("END", SCORE_MAX);
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struct ActionState {
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Action action;
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GOAPState state;
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ActionState(Action action, GOAPState state) :
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action(action), state(state) {}
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bool operator==(const ActionState& other) const {
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return other.action == action && other.state == state;
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}
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};
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bool is_subset(GOAPState& source, GOAPState& target);
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int distance_to_goal(GOAPState& from, GOAPState& to);
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std::optional<AStarPath> plan_actions(std::vector<Action>& actions, GOAPState& start, GOAPState& goal);
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}
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template<> struct std::hash<ailol::Action> {
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size_t operator()(const ailol::Action& p) const {
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return std::hash<std::string>{}(p.$name);
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}
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};
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template<> struct std::hash<ailol::ActionState> {
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size_t operator()(const ailol::ActionState& p) const {
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return std::hash<ailol::Action>{}(p.action) ^ std::hash<ailol::GOAPState>{}(p.state);
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}
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};
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