MultiObjectiveVariableElimination.hpp

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#ifndef AI_TOOLBOX_FACTORED_BANDIT_MULTI_OBJECTIVE_VARIABLE_ELIMINATION_HEADER_FILE
#define AI_TOOLBOX_FACTORED_BANDIT_MULTI_OBJECTIVE_VARIABLE_ELIMINATION_HEADER_FILE
 
#include <AIToolbox/Factored/Bandit/Types.hpp>
#include <AIToolbox/Factored/Utils/GenericVariableElimination.hpp>
 
namespace AIToolbox::Factored::Bandit {
    class MultiObjectiveVariableElimination {
        public:
            struct Entry {
                Rewards vals;
                PartialAction tag;
            };
            using Factor = std::vector<Entry>;
 
            using GVE = GenericVariableElimination<Factor>;
            using Results = Factor;
 
            template <typename Iterable>
            Results operator()(const Action & A, const Iterable & inputRules) {
                GVE::Graph graph(A.size());
 
                for (const auto & rule : inputRules) {
                    auto & factorNode = graph.getFactor(rule.action.first)->getData();
                    const auto id = toIndexPartial(A, rule.action);
 
                    const auto it = std::lower_bound(
                        std::begin(factorNode),
                        std::end(factorNode),
                        id,
                        [](const auto & rule, size_t rhs) {return rule.first < rhs;}
                    );
 
                    if (it != std::end(factorNode) && it->first == id)
                        it->second[0].vals += rule.values;
                    else
                        factorNode.emplace(it, id, Factor{{rule.values, PartialAction()}});
                }
 
                return (*this)(A, graph);
            }
 
            Results operator()(const Action & A, GVE::Graph & graph);
    };
}
 
#endif