Extract KnowledgeNetwork interfaces

SourceCode/Symu/Classes/Agents/Models/CognitiveModels/BeliefsModel.cs

@@ -15,6 +15,7 @@
 using Symu.Common.Interfaces.Entity;
 using Symu.Common.Math.ProbabilityDistributions;
 using Symu.Messaging.Templates;
+using Symu.Repository.Entity;
 using Symu.Repository.Networks;
 using Symu.Repository.Networks.Beliefs;
 using Symu.Repository.Networks.Knowledges;

SourceCode/Symu/Classes/Agents/Models/CognitiveModels/ForgettingModel.cs

@@ -16,6 +16,7 @@
 using Symu.Common;
 using Symu.Common.Interfaces.Entity;
 using Symu.Common.Math.ProbabilityDistributions;
+using Symu.Repository.Entity;
 using Symu.Repository.Networks.Knowledges;
 using static Symu.Common.Constants;
 
@@ -64,7 +65,7 @@ public float PercentageForgetting
         /// <returns></returns>
         public float GetKnowledgeSum()
         {
-            return Expertise.List.Sum(l => l.GetKnowledgeSum());
+            return Expertise.GetAgentKnowledges<AgentKnowledge>().Sum(l => l.GetKnowledgeSum());
         }
 
         public ForgettingModel(ModelEntity entity, bool knowledgeModelOn, CognitiveArchitecture cognitive,
@@ -213,7 +214,7 @@ public void InitializeForgettingProcess()
             }
 
             ForgettingExpertise.Clear();
-            foreach (var knowledge in Expertise.List)
+            foreach (var knowledge in Expertise.GetAgentKnowledges<AgentKnowledge>())
             {
                 ForgettingExpertise.Add(InitializeForgettingKnowledge(knowledge));
             }
@@ -232,7 +233,7 @@ public void FinalizeForgettingProcess(ushort step)
                 return;
             }
 
-            foreach (var forget in ForgettingExpertise.List)
+            foreach (var forget in ForgettingExpertise.GetAgentKnowledges<AgentKnowledge>())
             {
                 FinalizeForgettingKnowledge(forget, step);
             }
@@ -246,7 +247,7 @@ public void FinalizeForgettingKnowledge(AgentKnowledge forget, ushort step)
             }
 
             var forgetBits = forget.CloneBits();
-            var agentKnowledge = Expertise.GetKnowledge(forget.KnowledgeId);
+            var agentKnowledge = Expertise.GetAgentKnowledge<AgentKnowledge>(forget.KnowledgeId);
             switch (InternalCharacteristics.ForgettingSelectingMode)
             {
                 case ForgettingSelectingMode.Random:
@@ -372,13 +373,13 @@ public float[] InitializeForgettingKnowledgeRandom(AgentKnowledge agentKnowledge
         /// </summary>
         public void ForgettingProcess(float forgettingRate, ushort step)
         {
-            Expertise.List.ForEach(x => ForgettingProcess(x, forgettingRate, step));
+            Expertise.GetAgentKnowledges<AgentKnowledge>().ToList().ForEach(x => ForgettingProcess(x, forgettingRate, step));
         }
 
         /// <summary>
         ///     Forget knowledgeBits based on knowledgeBits.LastTouched and timeToLive value
         /// </summary>
-        public void ForgettingProcess(AgentKnowledge agentKnowledge, float forgettingRate, ushort step)
+        public static void ForgettingProcess(AgentKnowledge agentKnowledge, float forgettingRate, ushort step)
         {
             if (agentKnowledge == null)
             {
@@ -401,7 +402,7 @@ public void UpdateForgettingProcess(IId knowledgeId, byte[] workingBits)
                 throw new ArgumentNullException(nameof(workingBits));
             }
 
-            var forgettingKnowledge = ForgettingExpertise.GetKnowledge(knowledgeId);
+            var forgettingKnowledge = ForgettingExpertise.GetAgentKnowledge<AgentKnowledge>(knowledgeId);
             if (forgettingKnowledge == null)
             {
                 return;

SourceCode/Symu/Classes/Agents/Models/CognitiveModels/InfluenceModel.cs

@@ -13,6 +13,7 @@
 using Symu.Common.Interfaces.Agent;
 using Symu.Common.Interfaces.Entity;
 using Symu.Common.Math.ProbabilityDistributions;
+using Symu.Repository.Entity;
 using Symu.Repository.Networks;
 using Symu.Repository.Networks.Beliefs;
 using Symu.Repository.Networks.Influences;

SourceCode/Symu/Classes/Agents/Models/CognitiveModels/KnowledgeModel.cs

@@ -15,6 +15,7 @@
 using Symu.Common.Interfaces.Entity;
 using Symu.Common.Math.ProbabilityDistributions;
 using Symu.Messaging.Templates;
+using Symu.Repository.Entity;
 using Symu.Repository.Networks;
 using Symu.Repository.Networks.Knowledges;
 using static Symu.Common.Constants;
@@ -100,7 +101,7 @@ public class KnowledgeModel
         /// <returns></returns>
         public float GetKnowledgeSum()
         {
-            return Expertise.List.Sum(l => l.GetKnowledgeSum());
+            return Expertise.GetAgentKnowledges<AgentKnowledge>().Sum(l => l.GetKnowledgeSum());
         }
 
         /// <summary>
@@ -109,7 +110,7 @@ public float GetKnowledgeSum()
         /// <returns></returns>
         public float GetKnowledgePotential()
         {
-            return Expertise.List.Sum(l => l.GetKnowledgePotential());
+            return Expertise.GetAgentKnowledges<AgentKnowledge>().Sum(l => l.GetKnowledgePotential());
         }
         /// <summary>
         ///     Percentage of all Knowledge of the agent for all knowledge during the simulation
@@ -135,7 +136,7 @@ public float PercentageKnowledge
         /// </summary>
         public float Obsolescence(float step)
         {
-            return Expertise.List.Any() ? Expertise.List.Average(t => t.KnowledgeBits.Obsolescence(step)) : 0;
+            return Expertise.List.Any() ? Expertise.GetAgentKnowledges<AgentKnowledge>().Average(t => t.KnowledgeBits.Obsolescence(step)) : 0;
         }
         #endregion
 
@@ -151,7 +152,37 @@ public void InitializeExpertise(ushort step)
             }
 
             _knowledgeNetwork.AddAgentId(_agentId, Expertise);
-            _knowledgeNetwork.InitializeExpertise(_agentId, !_knowledgeAndBeliefs.HasInitialKnowledge, step);
+            //_knowledgeNetwork.InitializeExpertise(_agentId, !_knowledgeAndBeliefs.HasInitialKnowledge, step);
+
+            foreach (var agentKnowledge in _knowledgeNetwork.GetAgentExpertise(_agentId).List)
+            {
+                InitializeAgentKnowledge((AgentKnowledge)agentKnowledge, !_knowledgeAndBeliefs.HasInitialKnowledge, step);
+            }
+        }
+
+
+
+        /// <summary>
+        ///     Initialize AgentExpertise with a stochastic process based on the agent knowledge level
+        /// </summary>
+        /// <param name="agentKnowledge">AgentKnowledge to initialize</param>
+        /// <param name="neutral">if !HasInitialKnowledge, then a neutral (KnowledgeLevel.NoKnowledge) initialization is done</param>
+        /// <param name="step"></param>
+        public void InitializeAgentKnowledge(AgentKnowledge agentKnowledge, bool neutral, ushort step)
+        {
+            if (agentKnowledge is null)
+            {
+                throw new ArgumentNullException(nameof(agentKnowledge));
+            }
+
+            var knowledge = GetKnowledge(agentKnowledge.KnowledgeId);
+            if (knowledge == null)
+            {
+                throw new ArgumentNullException(nameof(knowledge));
+            }
+
+            var level = neutral ? KnowledgeLevel.NoKnowledge : agentKnowledge.KnowledgeLevel;
+            agentKnowledge.InitializeKnowledge(knowledge.Length, _knowledgeNetwork.Model, level, step);
         }
 
         /// <summary>
@@ -161,7 +192,7 @@ public void InitializeExpertise(ushort step)
         /// <param name="step"></param>
         public void InitializeKnowledge(IId knowledgeId, ushort step)
         {
-            _knowledgeNetwork.InitializeAgentKnowledge(GetKnowledge(knowledgeId),
+            InitializeAgentKnowledge(GetAgentKnowledge(knowledgeId),
                 !_knowledgeAndBeliefs.HasInitialKnowledge, step);
         }
 
@@ -211,7 +242,8 @@ public void AddKnowledge(IId knowledgeId, KnowledgeLevel level, float minimumKno
                 return;
             }
 
-            _knowledgeNetwork.Add(_agentId, knowledgeId, level, minimumKnowledge, timeToLive);
+            var agentKnowledge = new AgentKnowledge(knowledgeId, level, minimumKnowledge, timeToLive);
+            _knowledgeNetwork.Add(_agentId, agentKnowledge);
         }
 
 
@@ -246,7 +278,7 @@ public void AddKnowledge(IId knowledgeId, KnowledgeLevel level, float minimumKno
                 return null;
             }
 
-            var agentKnowledge = Expertise.GetKnowledge(knowledgeId);
+            var agentKnowledge = GetAgentKnowledge(knowledgeId);
             if (agentKnowledge is null)
             {
                 throw new ArgumentNullException(nameof(agentKnowledge));
@@ -287,9 +319,14 @@ public void AddKnowledge(IId knowledgeId, KnowledgeLevel level, float minimumKno
             return Math.Abs(bitsToSend.GetSum()) < Tolerance ? null : bitsToSend;
         }
 
-        public AgentKnowledge GetKnowledge(IId knowledgeId)
+        public AgentKnowledge GetAgentKnowledge(IId knowledgeId)
+        {
+            return Expertise.GetAgentKnowledge<AgentKnowledge>(knowledgeId);
+        }
+
+        public Knowledge GetKnowledge(IId knowledgeId)
         {
-            return Expertise.GetKnowledge(knowledgeId);
+            return _knowledgeNetwork.GetKnowledge<Knowledge>(knowledgeId);
         }
 
         #region KnowsEnough
@@ -341,8 +378,7 @@ public bool KnowsEnough(IId knowledgeId, byte knowledgeBit, float knowledgeThres
                 return false;
             }
 
-            var knowledge = GetKnowledge(knowledgeId);
-            return KnowsEnough(knowledge, knowledgeBit, knowledgeThreshHoldForAnswer, step);
+            return KnowsEnough(GetAgentKnowledge(knowledgeId), knowledgeBit, knowledgeThreshHoldForAnswer, step);
         }
 
         /// <summary>

SourceCode/Symu/Classes/Agents/Models/CognitiveModels/LearningModel.cs

@@ -16,6 +16,7 @@
 using Symu.Common.Interfaces.Agent;
 using Symu.Common.Interfaces.Entity;
 using Symu.Common.Math.ProbabilityDistributions;
+using Symu.Repository.Entity;
 using Symu.Repository.Networks.Knowledges;
 using static Symu.Common.Constants;
 
@@ -63,7 +64,7 @@ public float PercentageLearning
         /// <returns></returns>
         public float GetKnowledgePotential()
         {
-            return Expertise.List.Sum(l => l.GetKnowledgePotential());
+            return Expertise.GetAgentKnowledges<AgentKnowledge>().Sum(l => l.GetKnowledgePotential());
         }
 
         public LearningModel(AgentId agentId, OrganizationModels models, KnowledgeNetwork knowledgeNetwork,
@@ -165,8 +166,8 @@ public void Learn(IId knowledgeId, Bits knowledgeBits, float maxRateLearnable, u
                 throw new ArgumentNullException(nameof(knowledgeBits));
             }
 
-            _knowledgeNetwork.LearnNewKnowledge(_id, knowledgeId, minimumKnowledge, timeToLive, step);
-            var agentKnowledge = Expertise.GetKnowledge(knowledgeId);
+            LearnNewKnowledge(_id, knowledgeId, minimumKnowledge, timeToLive, step);
+            var agentKnowledge = Expertise.GetAgentKnowledge<AgentKnowledge>(knowledgeId);
             Learn(knowledgeBits, maxRateLearnable, agentKnowledge, step);
         }
 
@@ -225,8 +226,8 @@ public float Learn(IId knowledgeId, byte knowledgeBit, float minimumKnowledge, s
                 return 0;
             }
 
-            _knowledgeNetwork.LearnNewKnowledge(_id, knowledgeId, minimumKnowledge, timeToLive, step);
-            return AgentKnowledgeLearn(Expertise.GetKnowledge(knowledgeId), knowledgeBit, NextLearning(), step);
+            LearnNewKnowledge(_id, knowledgeId, minimumKnowledge, timeToLive, step);
+            return AgentKnowledgeLearn(Expertise.GetAgentKnowledge<AgentKnowledge>(knowledgeId), knowledgeBit, NextLearning(), step);
         }
 
         /// <summary>
@@ -291,8 +292,8 @@ public float LearnByDoing(IId knowledgeId, byte knowledgeBit, ushort step)
                 return 0;
             }
 
-            _knowledgeNetwork.LearnNewKnowledge(_id, knowledgeId, minimumKnowledge, timeToLive, step);
-            return AgentKnowledgeLearn(Expertise.GetKnowledge(knowledgeId), knowledgeBit, NextLearningByDoing(), step);
+            LearnNewKnowledge(_id, knowledgeId, minimumKnowledge, timeToLive, step);
+            return AgentKnowledgeLearn(Expertise.GetAgentKnowledge<AgentKnowledge>(knowledgeId), knowledgeBit, NextLearningByDoing(), step);
         }
 
         public float NextLearning()
@@ -325,6 +326,27 @@ public float NextLearningByDoing()
                 LearningStandardDeviationValue(TasksAndPerformance.LearningStandardDeviation);
             return TasksAndPerformance.LearningByDoingRate * Normal.Sample(1, stdDev * _randomLevel);
         }
+        /// <summary>
+        ///     Agent don't have still this Knowledge, it's time to create one
+        /// </summary>
+        /// <param name="agentId"></param>
+        /// <param name="knowledgeId"></param>
+        /// <param name="minimumKnowledge"></param>
+        /// <param name="timeToLive"></param>
+        /// <param name="step"></param>
+        public void LearnNewKnowledge(IAgentId agentId, IId knowledgeId, float minimumKnowledge, short timeToLive,
+            ushort step)
+        {
+            if (_knowledgeNetwork.Exists(agentId, knowledgeId))
+            {
+                return;
+            }
+
+            var agentKnowledge = new AgentKnowledge(knowledgeId, KnowledgeLevel.NoKnowledge, minimumKnowledge, timeToLive);
+            _knowledgeNetwork.Add(agentId, agentKnowledge);
+            var knowledge = _knowledgeNetwork.GetKnowledge<Knowledge>(knowledgeId);
+            agentKnowledge.InitializeKnowledge(knowledge.Length, _knowledgeNetwork.Model, KnowledgeLevel.NoKnowledge, step);
+        }
 
         private static float LearningStandardDeviationValue(GenericLevel level)
         {

SourceCode/Symu/Classes/Agents/Models/CognitiveModels/MessageContent.cs

@@ -10,6 +10,7 @@
 #region using directives
 
 using System;
+using Symu.Repository.Entity;
 using Symu.Repository.Networks.Knowledges;
 
 #endregion

SourceCode/Symu/Classes/Murphies/MurphyIncompleteKnowledge.cs

@@ -13,6 +13,7 @@
 using Symu.Classes.Agents.Models.CognitiveModels;
 using Symu.Classes.Task;
 using Symu.Common.Interfaces.Entity;
+using Symu.Repository.Entity;
 using Symu.Repository.Networks.Knowledges;
 
 #endregion
@@ -59,7 +60,7 @@ public class MurphyIncompleteKnowledge : MurphyIncomplete
             }
 
             // agent may don't have the knowledge at all
-            var workerKnowledge = knowledgeModel.Expertise.GetKnowledge(knowledgeId);
+            var workerKnowledge = knowledgeModel.Expertise.GetAgentKnowledge<AgentKnowledge>(knowledgeId);
             if (workerKnowledge == null)
             {
                 return;

SourceCode/Symu/Classes/Task/MurphyTask.cs

@@ -13,6 +13,7 @@
 using Symu.Classes.Murphies;
 using Symu.Common.Interfaces.Entity;
 using Symu.Common.Math.ProbabilityDistributions;
+using Symu.Repository.Entity;
 using Symu.Repository.Networks.Knowledges;
 using static Symu.Common.Constants;
 
@@ -127,7 +128,7 @@ public float MandatoryBitsRatio(float level)
         ///     complexity = 0.3
         ///     GetTaskRequiredBits = [359] : index 3, 5 and 9 are required
         /// </example>
-        public byte[] GetTaskRequiredBits(IKnowledge knowledge, float complexity)
+        public byte[] GetTaskRequiredBits(Knowledge knowledge, float complexity)
         {
             if (knowledge is null || knowledge.Length == 0)
             {
@@ -152,7 +153,7 @@ public byte[] GetTaskRequiredBits(IKnowledge knowledge, float complexity)
         ///     complexity = 0.2
         ///     GetTaskMandatoryBits = [17] : index 1 and 7 are mandatory
         /// </example>
-        public byte[] GetTaskMandatoryBits(IKnowledge knowledge, float complexity)
+        public byte[] GetTaskMandatoryBits(Knowledge knowledge, float complexity)
         {
             if (knowledge is null || knowledge.Length == 0)
             {

SourceCode/Symu/Classes/Task/SymuTask.cs

@@ -18,6 +18,7 @@
 using Symu.Common;
 using Symu.Common.Interfaces.Agent;
 using Symu.Common.Interfaces.Entity;
+using Symu.Repository.Entity;
 using Symu.Repository.Networks.Knowledges;
 using Symu.Results.Blocker;
 using static Symu.Common.Constants;
@@ -196,7 +197,7 @@ public void SetKnowledgesBits(MurphyTask model, IEnumerable<IKnowledge> knowledg
                 throw new ArgumentNullException(nameof(knowledges));
             }
 
-            foreach (var knowledge in knowledges)
+            foreach (var knowledge in knowledges.Cast<Knowledge>())
             {
                 var bit = new TaskKnowledgeBits
                 {

SourceCode/Symu/Messaging/Messages/MessageAttachments.cs

@@ -12,6 +12,7 @@
 using System;
 using System.Collections.Generic;
 using Symu.Common.Interfaces.Entity;
+using Symu.Repository.Entity;
 using Symu.Repository.Networks.Knowledges;
 
 #endregion

SourceCode/Symu/Messaging/Templates/CommunicationTemplate.cs

@@ -12,6 +12,7 @@
 using System;
 using Symu.Common;
 using Symu.Common.Math.ProbabilityDistributions;
+using Symu.Repository.Entity;
 using Symu.Repository.Networks.Knowledges;
 
 #endregion