text: exports.newFoundationsBotModulesLearningSystem = function (processIndex) {
      /*
      The Learning System is the user defined set of rules compliant with the Learning Protocol that
      defines the learning logic to be applied during each cycle of the Simulation.
      */
      const MODULE_NAME = 'Learning System'
      let thisObject = {
          loadModel: loadModel, 
          saveModel: saveModel, 
          mantain: mantain,
          reset: reset,
          run: run,
          updateChart: updateChart,
          initialize: initialize,
          finalize: finalize
      }
  
      /* 
      These 3 are the main data structures available to users
      when writing conditions and formulas.
      */
      let chart
      let exchange
      let market
  
      let learningSystem
      let learningEngine
      let sessionParameters
      let dynamicIndicators
  
      let machineLearningLibraryModuleObject
  
      return thisObject
  
      function initialize() {
          learningSystem = TS.projects.foundations.globals.processVariables.VARIABLES_BY_PROCESS_INDEX_MAP.get(processIndex).SIMULATION_STATE.learningSystem
          learningEngine = TS.projects.foundations.globals.processVariables.VARIABLES_BY_PROCESS_INDEX_MAP.get(processIndex).SIMULATION_STATE.learningEngine
          sessionParameters = TS.projects.foundations.globals.processConstants.CONSTANTS_BY_PROCESS_INDEX_MAP.get(processIndex).SESSION_NODE.learningParameters
  
          learningSystem.conditions = new Map()
          learningSystem.formulas = new Map()
  
          /* Adding Functions used elsewhere to Learning System Definition */
          learningSystem.checkConditions = function (situation, passed) {
              /* Given a Situation, we check if all children conditions are true or not */
              for (let m = 0; m < situation.conditions.length; m++) {
  
                  let condition = situation.conditions[m]
                  let value = false
                  if (learningSystem.conditions.get(condition.id) !== undefined) {
                      value = learningSystem.conditions.get(condition.id)
                  }
                  if (value === true) {
                      learningSystem.highlights.push(condition.id)
                  }
                  else {
                      passed = false
                  }
                  learningSystem.values.push([condition.id, value])
              }
              return passed
          }
  
          learningSystem.evalConditions = function (startingNode, descendentOfNodeType) {
              evalNode(startingNode, 'Conditions', descendentOfNodeType)
          }
  
          learningSystem.evalFormulas = function (startingNode, descendentOfNodeType) {
              evalNode(startingNode, 'Formulas', descendentOfNodeType)
          }
  
          learningSystem.addError = function (errorDataArray) {
              /*
              This function adds to the array of error info a rate.
              This rate will later help plotting the error at the
              charts.
              */
              let rate = learningEngine.learningCurrent.learningEpisode.candle.close.value
              errorDataArray.push(rate)
              learningSystem.errors.push(errorDataArray)
          }
  
          learningSystem.addWarning = function (warningDataArray) {
              /*
              This function adds to the array of warning info a rate. 
              This rate will later help plotting the warning at the
              charts.
              */
              let rate = learningEngine.learningCurrent.learningEpisode.candle.close.value
              warningDataArray.push(rate)
              learningSystem.warnings.push(warningDataArray)
          }
  
          learningSystem.addInfo = function (infoDataArray) {
              /*
              This function adds to the array of warning info a rate. 
              This rate will later help plotting the warning at the
              charts.
              */
              let rate = learningEngine.learningCurrent.learningEpisode.candle.close.value
              infoDataArray.push(rate)
              learningSystem.infos.push(infoDataArray)
          }
  
          /*
          Initialize the Machine Learning Library
          */
  
          let machineLearningLibrary = learningSystem.machineLearningLibrary
  
          if (machineLearningLibrary === undefined) {
              // TODO 
          }
          /* 
          We will scan the project schema until we find the machine learning library
          defined by the user at the UI.
          */
          for (let i = 0; i < TS.projects.foundations.globals.taskConstants.PROJECTS_SCHEMA.length; i++) {
              let projectSchemaProject = TS.projects.foundations.globals.taskConstants.PROJECTS_SCHEMA[i]
              if (projectSchemaProject.name !== machineLearningLibrary.project) { continue }
  
              for (let j = 0; j < projectSchemaProject.TS.botModules.length; j++) {
                  let botModuleDefinition = projectSchemaProject.TS.botModules[j]
  
                  /* 
                  We match the type of the machine learning library with the name at the project schema 
                  */
                  if (botModuleDefinition.name === machineLearningLibrary.type) {
  
                      let project = TS.projects[machineLearningLibrary.project.toLowerCase()]
                      let botModule = project.botModules[botModuleDefinition.propertyName]
                      let moduleFunction = botModule[botModuleDefinition.functionName]
                      machineLearningLibraryModuleObject = moduleFunction(processIndex)
                  }
              }
          }
          machineLearningLibraryModuleObject.initialize(onInitializeReady)
  
          function onInitializeReady(err) {
              if (err.result === TS.projects.foundations.globals.standardResponses.DEFAULT_OK_RESPONSE.result) {
  
              } else {
  
              }
          }
  
          function isItInside(elementWithTimestamp, elementWithBeginEnd) {
              /* 
              The function is to allow in Conditions and Formulas to easily 
              know when an element with timestamp (like the ones of 
              single files) are inside the time range
              of an element with a time range, like a candle.
              */
              if (elementWithTimestamp.timestamp >= elementWithBeginEnd.begin && elementWithTimestamp.timestamp <= elementWithBeginEnd.end) {
                  return true
              } else {
                  return false
              }
          }
      }
  
      function finalize() {
  
          machineLearningLibraryModuleObject.finalize()
          machineLearningLibraryModuleObject = undefined
  
          chart = undefined
          exchange = undefined
          market = undefined
  
          learningSystem.conditions = undefined
          learningSystem.formulas = undefined
  
          learningSystem.highlights = undefined
          learningSystem.errors = undefined
          learningSystem.warnings = undefined
          learningSystem.infos = undefined
          learningSystem.values = undefined
          learningSystem.status = undefined
          learningSystem.progress = undefined
          learningSystem.running = undefined
  
          learningSystem = undefined
          learningEngine = undefined
          sessionParameters = undefined
      }
      
      async function  loadModel() {
          await machineLearningLibraryModuleObject.loadModel()
      }
  
      async function  saveModel() {
          await machineLearningLibraryModuleObject.saveModel()
      }
  
      function mantain() {
          machineLearningLibraryModuleObject.mantain()
      }
  
      function reset() {
          machineLearningLibraryModuleObject.reset()
  
          learningSystem.highlights = []
          learningSystem.errors = []
          learningSystem.warnings = []
          learningSystem.infos = []
          learningSystem.values = []
          learningSystem.status = []
          learningSystem.progress = []
          learningSystem.running = []
          learningSystem.announcements = []
      }
  
      function updateChart(pChart, pExchange, pMarket) {
          /* 
          We need these 3 data structures  to be a local objects 
          accessible while evaluating conditions and formulas.
          */
          chart = pChart
          exchange = pExchange
          market = pMarket
  
          machineLearningLibraryModuleObject.updateChart(pChart, pExchange, pMarket)
      }
  
      function buildDynamicIndicators() {
          if (learningSystem.dynamicIndicators !== undefined) {
              dynamicIndicators = {}
              /* Eval Dynamic Indicators */
              learningSystem.evalFormulas(learningSystem.dynamicIndicators, 'Indicator Function')
  
              for (let i = 0; i < learningSystem.dynamicIndicators.indicatorFunctions.length; i++) {
                  let indicatorFunction = learningSystem.dynamicIndicators.indicatorFunctions[i]
                  if (indicatorFunction.formula === undefined) { return }
                  if (indicatorFunction.config.codeName === undefined) { return }
                  dynamicIndicators[indicatorFunction.config.codeName] = learningSystem.formulas.get(indicatorFunction.formula.id)
              }
          }
      }
  
      async function run() {
          try {
              /* Dynamic Indicators */
              buildDynamicIndicators()
  
              /*
              Initialize the Learning Algorithm
              */
              await machineLearningLibraryModuleObject.run()
  
          } catch (err) {
              /* 
              If an error ocurred during execution, it was alreeady logged and
              included at the errors array. That means we need to do nothing here,
              just prevent the execution to be halted for not handling exceptions.
              */
              if (typeof err === 'string' || err instanceof String) {
                  TS.projects.foundations.globals.loggerVariables.VARIABLES_BY_PROCESS_INDEX_MAP.get(processIndex).BOT_MAIN_LOOP_LOGGER_MODULE_OBJECT.write(MODULE_NAME, '[ERROR] runExecution -> err = ' + err)
              }
              if (err.stack !== undefined) {
                  TS.projects.foundations.globals.loggerVariables.VARIABLES_BY_PROCESS_INDEX_MAP.get(processIndex).BOT_MAIN_LOOP_LOGGER_MODULE_OBJECT.write(MODULE_NAME, '[ERROR] runExecution -> err = ' + err.stack)
              }
          }
      }
  
      function evalNode(node, evaluating, descendentOfNodeType, isDescendent) {
          if (node === undefined) { return }
  
          /* Verify if this node is decendent of the specified node type */
          if (isDescendent !== true) {
              if (node.type === descendentOfNodeType) {
                  isDescendent = true
              }
          }
  
          /* Here we check if there is a codition to be evaluated */
          if (node.type === 'Condition' && evaluating === 'Conditions') {
              /* We will eval this condition */
              if (isDescendent === true) {
                  evalCondition(node)
              }
          }
  
          /* Here we check if there is a formula to be evaluated */
          if ((node.type === 'Feature Formula' || node.type === 'Label Formula') && evaluating === 'Formulas') {
              if (node.code !== undefined) {
                  /* We will eval this formula */
                  if (isDescendent === true) {
                      evalFormula(node)
                  }
              }
          }
  
          /* Now we go down through all this node children */
          let schemaDocument = TS.projects.foundations.globals.taskConstants.APP_SCHEMA_MAP.get(node.project + '-' + node.type)
          if (schemaDocument === undefined) { return }
  
          if (schemaDocument.childrenNodesProperties !== undefined) {
              let previousPropertyName // Since there are cases where there are many properties with the same name,because they can hold nodes of different types but only one at the time, we have to avoind counting each property of those as individual children.
              for (let i = 0; i < schemaDocument.childrenNodesProperties.length; i++) {
                  let property = schemaDocument.childrenNodesProperties[i]
  
                  switch (property.type) {
                      case 'node': {
                          if (property.name !== previousPropertyName) {
                              if (node[property.name] !== undefined) {
                                  evalNode(node[property.name], evaluating, descendentOfNodeType, isDescendent)
                              }
                              previousPropertyName = property.name
                          }
                          break
                      }
                      case 'array': {
                          if (node[property.name] !== undefined) {
                              let nodePropertyArray = node[property.name]
                              for (let m = 0; m < nodePropertyArray.length; m++) {
                                  evalNode(nodePropertyArray[m], evaluating, descendentOfNodeType, isDescendent)
                              }
                          }
                          break
                      }
                  }
              }
          }
      }
  
      function evalCondition(node) {
          let value
          let errorMessage
          let docs
          /*
          The code can be at the condition node if it was done with the Conditions Editor, or it can also be
          at a Javascript Code node. If there is a Javascript object we will give it preference and take the code
          from there. Otherwise we will take the code from the Condition node.
          */
          let code = node.code
          let nodeName = node.name
          if (node.javascriptCode !== undefined) {
              if (node.javascriptCode.code !== undefined) {
                  code = node.javascriptCode.code
                  nodeName = node.javascriptCode.name
              }
          }
  
          try {
              TS.projects.foundations.globals.loggerVariables.VARIABLES_BY_PROCESS_INDEX_MAP.get(processIndex).BOT_MAIN_LOOP_LOGGER_MODULE_OBJECT.write(MODULE_NAME, '[INFO] evalCondition -> ' + node.name + ' -> code = ' + code)
              value = eval(code)
          } catch (err) {
              /*
                  One possible error is that the conditions references a .previous that is undefined. This
                  will not be considered an error.
              */
              value = false
              errorMessage = err.message
              docs = {
                  project: 'Foundations',
                  category: 'Topic',
                  type: 'TS LF Learning Bot Error - Evaluating Condition Error',
                  placeholder: {}
              }
              TS.projects.education.utilities.docsFunctions.buildPlaceholder(docs, err, nodeName, code, undefined)
          }
  
          learningSystem.conditions.set(node.id, value)
  
          if (value === true) {
              learningSystem.highlights.push(node.id)
          }
          if (errorMessage !== undefined) {
              learningSystem.addError([node.id, errorMessage, docs])
          }
          if (value !== undefined) {
              learningSystem.values.push([node.id, value])
          }
  
          TS.projects.foundations.globals.loggerVariables.VARIABLES_BY_PROCESS_INDEX_MAP.get(processIndex).BOT_MAIN_LOOP_LOGGER_MODULE_OBJECT.write(MODULE_NAME, '[INFO] evalCondition -> value = ' + value)
          TS.projects.foundations.globals.loggerVariables.VARIABLES_BY_PROCESS_INDEX_MAP.get(processIndex).BOT_MAIN_LOOP_LOGGER_MODULE_OBJECT.write(MODULE_NAME, '[INFO] evalCondition -> errorMessage = ' + errorMessage)
      }
  
      function evalFormula(node) {
          let value
          let errorMessage
          let docs
  
          try {
              TS.projects.foundations.globals.loggerVariables.VARIABLES_BY_PROCESS_INDEX_MAP.get(processIndex).BOT_MAIN_LOOP_LOGGER_MODULE_OBJECT.write(MODULE_NAME, '[INFO] evalFormula -> ' + node.name + ' -> code = ' + node.code)
              value = eval(node.code)
          } catch (err) {
              /*
                  One possible error is that the formula references a .previous that is undefined. This
                  will not be considered an error.
              */
              value = 0
              errorMessage = err.message
              docs = {
                  project: 'Foundations',
                  category: 'Topic',
                  type: 'TS LF Learning Bot Error - Evaluating Formula Error',
                  placeholder: {}
              }
              TS.projects.education.utilities.docsFunctions.buildPlaceholder(docs, err, node.name, node.code, undefined)
          }
  
          if (errorMessage !== undefined) {
              learningSystem.addError([node.id, errorMessage, docs])
              TS.projects.foundations.globals.loggerVariables.VARIABLES_BY_PROCESS_INDEX_MAP.get(processIndex).BOT_MAIN_LOOP_LOGGER_MODULE_OBJECT.write(MODULE_NAME, '[INFO] evalFormula -> errorMessage = ' + errorMessage)
              return
          } else {
              if (value !== undefined) {
                  if ((node.type === 'Feature Formula' || node.type === 'Label Formula') && isNaN(value)) {
  
                      docs = {
                          project: 'Foundations',
                          category: 'Topic',
                          type: 'TS LF Learning Bot Error - Formula Value Not A Number',
                          placeholder: {}
                      }
                      TS.projects.education.utilities.docsFunctions.buildPlaceholder(docs, undefined, node.name, node.code, undefined, value)
  
                      learningSystem.addError([node.id, 'Formula needs to return a numeric value.', docs])
                      return
                  }
  
                  learningSystem.values.push([node.id, value])
                  learningSystem.formulas.set(node.id, value)
              }
          }
  
          TS.projects.foundations.globals.loggerVariables.VARIABLES_BY_PROCESS_INDEX_MAP.get(processIndex).BOT_MAIN_LOOP_LOGGER_MODULE_OBJECT.write(MODULE_NAME, '[INFO] evalFormula -> value = ' + value)
      }
  }
  
  