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Configuring the Adaptive Decision Manager service for on-premises environments

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Enable the prediction of customer behavior by configuring the Adaptive Decision Manager (ADM) service. The ADM service creates adaptive models and updates them in real time based on incoming customer responses to your offers. With adaptive models, you can ensure that your next-best-action decisions are always relevant and based on the latest customer behavior.

This procedure applies only to on-premises deployments.
  1. Enable the capturing of incoming customer responses by configuring the Decision Data Store service.

    For more information see Configuring the Decision Data Store service.

  2. Start the ADM service by assigning the ADM node type to two Pega Platform nodes.

    For more information, see Assigning node types to nodes for on-premises environments.

  1. In the header of Dev Studio, click Configure Decisioning Infrastructure Services Adaptive Decision Manager .

  2. In the Adaptive decision manager nodes section, click Edit settings.

  3. In the Edit adaptive decision manager settings dialog box, in the Snapshot section, specify what adaptive model data you want to save:

    • To take snapshots of all adaptive scoring data and only the latest predictor data, select Store all model data and only the latest predictor data.

      Select this option if you want to analyze only the most recent status of model predictor data (for example, by using a report definition).

    • To take snapshots of all adaptive scoring data and all predictor data, select Store all model data and all predictor data.

      Select this option to analyze the changes in model predictor data over time.

      If this option is enabled over a prolonged time period, the increased number of predictor snapshots might cause database space issues.
  4. In the Snapshot schedule section, specify how often you want to take snapshots of adaptive model data:

    • To take snapshots at a specified time interval, select Using agent schedule. To edit the time interval, click Edit agent schedule, and then specify the schedule for ADMSnapshot.

      For more information about configuring the agent schedule, see Completing the Schedule tab.

    • To take a snapshot every time that the model is updated, select At every model update.

      A model update includes every change that is made to the model, such as adding new training data or making a decision based on the model.

  5. In the Service configuration section, define the ADM service parameters:

    1. Specify how often you want to check for model updates.

      The time interval that you specify indicates how often Pega Platform checks if a model requires an update.
    2. In the Thread count field, enter the number of threads on all nodes that are running the ADM service.

      The default thread count is the number of available co-processes on that node, minus one.
    3. In the Memory alert threshold field, enter the threshold for triggering the out-of-memory error.

      The default memory alert threshold is 2048 megabytes.
  6. Confirm your settings by clicking Submit.

  7. To change how much time elapses before Pega Platform automatically deletes a snapshot from your repository, change the value of the decision/monitoring/daysToKeepData dynamic system setting.

    By default, Pega Platform deletes snapshots with a time stamp older than 180 days.

  • Optional: Configuring the Adaptive Decision Manager service for Pega Cloud Services

    The Adaptive Decision Manager (ADM) service provides predictions of customer behavior by creating adaptive models based on customer responses to your offers. With adaptive models, you can ensure that your next-best-action decisions are always relevant and based on the latest customer behavior.

  • Status parameters of Adaptive Decision Manager nodes

    The Adaptive Decision Manager (ADM) creates and updates adaptive models by processing customer responses in real time. By including adaptive models in your next-best-actions strategies, you can make better decisions for your business based on accurately predicted customer behavior. Use the following reference information to better understand the status parameters of ADM nodes.

  • Managing decision management nodes

    Manage the decision management nodes in your application by running certain actions for them, for example, repair or clean-up.

  • Enabling decision management services

    Decision management services comprise the technical foundation of decision management. Learn more about decision management services and how to enable them to fully benefit from next-best-action strategies and other decision management features in Pega Platform.

  • Adaptive analytics

    Adaptive Decision Manager (ADM) uses self-learning models to predict customer behavior. Adaptive models are used in decision strategies to increase the relevance of decisions.

  • Pega-DecisionEngine agents

    The Pega-DecisionEngine agents support Decision Management operations.

  • Model management

    On the Model Management landing page, you can manage adaptive models that were run and predictive models with responses. You can view the performance of individual models and the number of their responses, or perform various maintenance activities, such as clearing, deleting, and updating models.

  • Adaptive model details

    On the Model Management landing page, you can access details about the adaptive models that were executed (such as the number of recorded responses, last update time, and so on). The models are generated as a result of running a decision strategy that contains an Adaptive Model shape.

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