ParallelETUCT.hh

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#ifndef _ParallelETUCT_HH_
#define _ParallelETUCT_HH_

#include <rl_common/Random.h>
#include <rl_common/core.hh>
#include <rl_common/ExperienceFile.hh>

#include "../Models/FactoredModel.hh"
#include "../Models/C45Tree.hh"

#include <set>
#include <vector>
#include <map>
#include <sstream>
#include <deque>

void* parallelSearchStart(void* arg);

void* parallelModelLearningStart(void* arg);

class ParallelETUCT: public Planner {
public:


  ParallelETUCT(int numactions, float gamma, float rrange, float lambda,
                int MAX_ITER, float MAX_TIME, int MAX_DEPTH,  int modelType,
                const std::vector<float> &featmax, const std::vector<float> &featmin,
                 const std::vector<int> &statesPerDim, bool trackActual, int historySize, Random rng = Random());
  
  ParallelETUCT(const ParallelETUCT &);

  virtual ~ParallelETUCT();

  virtual void setModel(MDPModel* model);
  virtual bool updateModelWithExperience(const std::vector<float> &last, 
                                         int act, 
                                         const std::vector<float> &curr, 
                                         float reward, bool term);
  virtual void planOnNewModel();
  virtual int getBestAction(const std::vector<float> &s);

  virtual void setSeeding(bool seed);
  virtual void setFirst();

  bool PLANNERDEBUG;
  bool POLICYDEBUG; //= false; //true;
  bool MODELDEBUG;
  bool ACTDEBUG;
  bool UCTDEBUG;
  bool PTHREADDEBUG;
  bool ATHREADDEBUG;
  bool MTHREADDEBUG;
  bool TIMINGDEBUG;
  bool REALSTATEDEBUG;
  bool HISTORYDEBUG;

  MDPModel* model;

  MDPModel* modelcopy;

  typedef const std::vector<float> *state_t;

  // parallel stuff

  // tell if thread started
  bool modelThreadStarted;
  bool planThreadStarted;

  pthread_t planThread;

  pthread_t modelThread;

  // some variables that are locked
  std::vector<experience> expList;

  state_t discPlanState;
  
  std::vector<float> actualPlanState;

  state_t startState;

  // lock over simple objects
  pthread_mutex_t update_mutex;
  pthread_mutex_t plan_state_mutex;
  pthread_mutex_t model_mutex;
  pthread_mutex_t list_mutex;
  pthread_mutex_t history_mutex;
  pthread_mutex_t nactions_mutex;

  pthread_mutex_t statespace_mutex;

  // condition for when list is updated
  pthread_cond_t list_cond; 

  float uctSearch(const std::vector<float> &actS, state_t state, int depth, std::deque<float> &history);

  std::vector<float> selectRandomState();

  void parallelModelLearning();

  void parallelSearch();

  void loadPolicy(const char* filename);

  void logValues(ofstream *of, int xmin, int xmax, int ymin, int ymax);

  std::vector<float> addVec(const std::vector<float> &a, const std::vector<float> &b);

  std::vector<float> subVec(const std::vector<float> &a, const std::vector<float> &b);

protected:


  struct state_info;
  struct model_info;

  struct state_samples {
    std::vector<state_t> samples;
  };

  struct state_info {

    // data filled in from models
    std::map< std::deque<float>, StateActionInfo>* historyModel;

    // q values from policy creation
    std::vector<float> Q;

    // uct experience data
    int uctVisits;
    std::vector<int> uctActions;
    short unsigned int visited;
    short unsigned int id;

    // needs update
    bool needsUpdate;

    // mutex for model info, samples, everything else
    pthread_mutex_t statemodel_mutex;
    pthread_mutex_t stateinfo_mutex;

  };



  void initStateInfo(state_t s,state_info* info, int id);
  
  state_t canonicalize(const std::vector<float> &s);

  void deleteInfo(state_info* info);
  
  void createPolicy();
  
  void printStates();
  
  void calculateReachableStates();
  
  void removeUnreachableStates();

  void updateStateActionFromModel(state_t s, int a, state_info* info);
  
  void updateStateActionHistoryFromModel(const std::vector<float> modState, int a, StateActionInfo *newModel);

  double getSeconds();

  // uct stuff
  void resetAndUpdateStateActions();
  
  std::vector<float> simulateNextState(const std::vector<float> &actS, state_t state, state_info* info, const std::deque<float> &history, int action, float* reward, bool* term);
  
  int selectUCTAction(state_info* info);
  
  void canonNextStates(StateActionInfo* modelInfo);

  void initStates();
  
  void fillInState(std::vector<float>s, int depth);

  virtual void savePolicy(const char* filename);
  
  std::vector<float> discretizeState(const std::vector<float> &s);

private:

  std::set<std::vector<float> > statespace;

  std::map<state_t, state_info> statedata;

  std::vector<float> featmax;
  std::vector<float> featmin;

  std::deque<float> saHistory;

  state_t prevstate;
  int prevact;
  state_info* previnfo;

  double planTime;
  double initTime;
  double setTime;
  bool seedMode;

  int nstates;
  int nsaved;
  int nactions;
  int lastUpdate;

  bool timingType;

  const int numactions;
  const float gamma;
  const float rrange;
  const float lambda;

  const int MAX_ITER;
  const float MAX_TIME;
  const int MAX_DEPTH;
  const int modelType;
  const std::vector<int> &statesPerDim;
  const bool trackActual;
  const int HISTORY_SIZE;
  const int HISTORY_FL_SIZE;

  const unsigned CLEAR_SIZE;
  ExperienceFile expfile;
};

#endif