Course Overview
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Course Synopsis
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This course covers the advance topics of modeling and simulation such as Developing Models, Executing Simulations, Analyzing Results, Calibrating Models, Verification & Validation of Models
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Course Learning Outcomes
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At the end of this course students will have better understandings of followings:
- Basics of Simulation
- Statistical Models
- Formal Models
- Agent-Based Model
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Course Calendar
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Week 01
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2
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When simulation is the appropriate tool
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4
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Advantages and Disadvantage
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5
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Disadvantages of Simulation
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10
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Components of a system
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11
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Discrete and Continuous
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14
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Discrete Event Simulation
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15
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Steps in a sim. Study: Planning
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16
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Steps in a sim. Study: Conceptualization
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Week 02
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17
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Steps in a sim. Study: Data Collection and Model Translation
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18
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Steps in a sim. Study:Verification and Validation
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19
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Steps in a sim. Study:Experimental Design
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20
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Steps in a sim. Documentation
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21
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Steps in a sim. Study: Logs & Reports
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22
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Steps in a sim. Study: Phases Overview
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23
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Simulation Case Studies Basic steps
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24
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Basics of a Spreadsheet Simulation: Simulating Randomness
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25
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Simulating a Coin Toss
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26
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Simulating a Random Service Time
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27
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Simulating a Random Arrival Time
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28
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Framework for Spreadsheet Simulation
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29
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Framework Simulation Table Design
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30
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Framework using Discrete event simulation: General Idea
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31
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Framework using Discrete event simulation - I
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32
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Framework using Discrete event simulation - II
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Week 03
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33
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Framework using Discrete event simulation - III
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34
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Framework using Discrete event simulation - IV
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35
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Event Scheduling Time advance algo
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36
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Event Scheduling Time advance algo-II
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37
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Event Scheduling Time advance algo-III
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38
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Event Scheduling Time advance algo-IV
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44
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Statistical Models in Sim
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Week 04
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51
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Why Agent-Based Modeling?
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53
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Complex Systems and Emergence
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54
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Understanding Complex Systems and Emergence
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55
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Example 1: Integrative Understanding
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56
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Example 2: Differential Understanding
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57
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Agent-Based Modeling as Representational Infrastructure for Restructurations
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58
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Example: Predator-Prey Interactions
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60
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What Is Agent-Based Modeling?
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62
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Creating the Ant Foraging Model
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63
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Expressional ProteomicsResults and Observations from the Ant Model
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64
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What Good Is an Ant Model?
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Week 05
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65
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What Is Agent Based Modeling?
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66
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Agent-Based Models vs. Other Modeling Forms
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67
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Randomness vs. Determinism
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68
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When Is ABM Most Beneficial?
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70
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What Is Needed to Understand ABM?
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72
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Beginner NetLogo Explorations
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73
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Ants and Other Model Explorations
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77
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Creating Simple Agent-Based Models: Life-I
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Week 06
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85
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NetLogo: Agentsets and Lists
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86
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Exploring and Extending Agent-Based Models
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87
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Characteristic Features of ABM
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89
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Fire Model: Basic Model
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90
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First Extension: Probabilistic Transitions
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91
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Second Extension: Adding Wind
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92
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Third Extension: Allow Long-Distance Transmission
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93
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The Diffusion-Limited Aggregation (DLA) Model
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94
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First Extension: Probabilistic Sticking
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95
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Second Extension: Neighbor Influence
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96
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Third Extension: Different Aggregates
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Week 07
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98
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Description of the Segregation Model-I
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99
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Description of the Segregation Model-II
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100
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Simulation of the Segregation Model
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101
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First Extension: Adding Multiple Ethnicities
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102
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Second Extension: Allowing Diverse Thresholds
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103
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Third Extension: Adding Diversity-Seeking Individuals
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106
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First Extension: Color Agents that are more successful predictors
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107
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Second Extension: Average, Min and Max Rewards
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108
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Third Extension: Histogram reward vales
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109
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Advanced Modelling Applications
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110
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Creating Agent-based Model
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112
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Choosing Your Questions
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Week 08
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115
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Choosing Agent Properties
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116
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Choosing Agent Behavior Choosing Parameters of the Model
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117
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Choosing Parameters of Model
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118
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Summary of the Wolf Sheep Simple Model Design
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121
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Predator-Prey Models: Additional Context
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122
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Advanced Modeling Applications
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123
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The Components of Agent-Based Modeling
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125
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Properties & Behaviors
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126
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Collections of Agents
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127
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The Granularity of an Agent
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Week 09
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129
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Other Kinds of Agents
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132
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Network-Based Environments
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135
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Observer/User Interface
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137
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Analyzing Agent-Based Models
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138
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Types of Measurements
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139
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Modeling the Spread of Disease
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140
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Statistical Analysis of ABM: Moving beyond Raw Data
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141
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The Necessity of Multiple Runs within ABM
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142
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Using Graphs to Examine Results in ABM
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143
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Analyzing Networks within ABM
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144
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Environmental Data and ABM
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Week 10
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145
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Correctness of a Model
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148
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Describing Conceptual Models
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151
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Sensitivity Analysis and Robustness
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152
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Verification Benefits and Issues
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154
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Macrovalidation vs. Microvalidation
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155
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Face Validation vs. Empirical Validation
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156
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Validation Benefits and Questions
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158
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Replication of Computational Models: Dimensions and Standards
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159
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Benefits of replication
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160
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Recommendations For Model Replicators
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Week 11
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161
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Recommendations for Model Authors
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162
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Complex Adaptive Systems
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169
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Complex Network-based Modeling
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170
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Cognitive Agent-based Computing Framework
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171
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Useful Statistical Models
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172
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Bernoulli Distribution
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173
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Binomial Distribution
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176
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Exponential Distribution
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Week 12
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177
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Triangular Distribution
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178
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CHARACTERISTICS OF QUEUEING SYSTEMS
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179
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The Calling Population
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182
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QUEUE BEHAVIOR AND QUEUE DISCIPLINE
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183
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Service Times and the Service Mechanism
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185
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Long-run Measures Of Performance Of Queueing Systems
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186
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Properties Of Random Numbers
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187
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Linear Congruential Method
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188
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Generation Of Pseudo-random Numbers
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189
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Tests for Random numbers
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190
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Random Variate Generation
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191
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Inverse Transform Technique
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192
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Acceptance Rejection Technique
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Week 13
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193
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Other topics in Randomness
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195
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Identifying the Distribution with Data
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197
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Selecting the Family of Distributions
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198
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Quantile-Quantile Plot
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200
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Preliminary Statistics: Sample Mean and Sample Variance
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201
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Evolution of Computer Systems Architectures
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202
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Evolution of Database Systems
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203
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Evolution of Operating Systems
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204
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Evolution of Computer Networks
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205
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Need for Performance Evaluation
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206
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Role of Performance Evaluation in Computer Engineering
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207
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Overview of Performance Evaluation Methods
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208
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Performance Metrics and Evaluation Criteria
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Week 14
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209
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Comparison of Two System Designs
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210
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Independent Sampling with Equal Variances
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211
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Independent Sampling with Unequal Variances
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212
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Common Random Numbers
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213
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Confidence Intervals with Specified Precision
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214
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Comparison of Several System Designs
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215
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Bonferroni Approach to Multiple Comparisons
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216
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Bonferroni Approach to Selecting the Best
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217
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Bonferroni Approach to Screening
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219
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Simple Linear Regression
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220
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Testing for Significance of Regression
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221
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What Does 'Optimization via Simulation' Mean?
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222
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Difficulties in Optimization via Simulation
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223
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Using Robust Heuristics
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224
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Random Search: An Illustration
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225
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Introduction to performance evaluation
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Week 15
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227
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Measurements (sampling)
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233
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Problems encountered in model development and use
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235
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Introduction to Software Reliability
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236
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Definitions and Software Reliability Model
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237
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Software Reliability Growth Modeling
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238
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Imperfect Debugging Modeling
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239
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Imperfect Debugging Model with Perfect Correction Rate
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240
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Imperfect Debugging with Introduced Faults
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241
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Software Availability Modeling
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Week 16
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243
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Software Availability Measures
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244
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Application of Software Reliability Assessment
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245
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Optimal Software Release Problem
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246
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Statistical Software Testing-Progress Control
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247
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Optimal Testing-Effort Allocation
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248
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Introduction to formal modeling
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251
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Classical Petri Nets-I
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252
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Classical Petri Nets-????
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255
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Priority-based Petri nets
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257
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Generalized Petri nets
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