text: /* * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * */
  /*                                                                           */
  /*                  This file is part of the program and library             */
  /*         SCIP --- Solving Constraint Integer Programs                      */
  /*                                                                           */
  /*    Copyright (C) 2002-2021 Konrad-Zuse-Zentrum                            */
  /*                            fuer Informationstechnik Berlin                */
  /*                                                                           */
  /*  SCIP is distributed under the terms of the ZIB Academic License.         */
  /*                                                                           */
  /*  You should have received a copy of the ZIB Academic License              */
  /*  along with SCIP; see the file COPYING. If not visit scipopt.org.         */
  /*                                                                           */
  /* * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * * */
  
  /**@file   pub_bandit_epsgreedy.h
   * @ingroup PublicBanditMethods
   * @brief  public methods for the epsilon greedy bandit selector
   * @author Gregor Hendel
   */
  
  /*---+----1----+----2----+----3----+----4----+----5----+----6----+----7----+----8----+----9----+----0----+----1----+----2*/
  
  #ifndef SRC_SCIP_PUB_BANDIT_EPSGREEDY_H_
  #define SRC_SCIP_PUB_BANDIT_EPSGREEDY_H_
  
  
  #include "scip/def.h"
  #include "scip/type_scip.h"
  #include "scip/type_bandit.h"
  
  #ifdef __cplusplus
  extern "C" {
  #endif
  
  /**@addtogroup PublicBanditMethods
   *
   * ## Epsilon greedy
   *
   * Epsilon greedy is a randomized algorithm for the multi-armed bandit problem.
   *
   * In every iteration, it either
   * selects an action uniformly at random with
   * probability \f$ \varepsilon_t\f$
   * or it greedily exploits the best action seen so far with
   * probability \f$ 1 - \varepsilon_t \f$.
   * In this implementation, \f$ \varepsilon_t \f$ decreases over time
   * (number of selections performed), controlled by the epsilon parameter.
   *
   * @{
   */
  
  /** create and resets an epsilon greedy bandit algorithm */
  SCIP_EXPORT
  SCIP_RETCODE SCIPcreateBanditEpsgreedy(
     SCIP*                 scip,               /**< SCIP data structure */
     SCIP_BANDIT**         epsgreedy,          /**< pointer to store the epsilon greedy bandit algorithm */
     SCIP_Real*            priorities,         /**< nonnegative priorities for each action, or NULL if not needed */
     SCIP_Real             eps,                /**< parameter to increase probability for exploration between all actions */
     SCIP_Bool             preferrecent,       /**< should the weights be updated in an exponentially decaying way? */
     SCIP_Real             decayfactor,        /**< the factor to reduce the weight of older observations if exponential decay is enabled */
     int                   avglim,             /**< nonnegative limit on observation number before the exponential decay starts,
                                                 *  only relevant if exponential decay is enabled
                                                 */
     int                   nactions,           /**< the number of possible actions */
     unsigned int          initseed            /**< initial seed for random number generation */
     );
  
  /** get weights array of epsilon greedy bandit algorithm */
  SCIP_EXPORT
  SCIP_Real* SCIPgetWeightsEpsgreedy(
     SCIP_BANDIT*          epsgreedy           /**< epsilon greedy bandit algorithm */
     );
  
  /** set epsilon parameter of epsilon greedy bandit algorithm */
  SCIP_EXPORT
  void SCIPsetEpsilonEpsgreedy(
     SCIP_BANDIT*          epsgreedy,          /**< epsilon greedy bandit algorithm */
     SCIP_Real             eps                 /**< parameter to increase probability for exploration between all actions */
     );
  
  /** @} */
  
  
  
  #ifdef __cplusplus
  }
  #endif
  
  #endif
  