{"product_id":"modeling-humansystem-interaction-9781119275268","title":"Modeling HumanSystem Interaction","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cp\u003eThis book presents theories and models to examine how humans interact with complex automated systems, including both empirical and theoretical methods.\u003c\/p\u003e \u003cul\u003e \u003cli\u003eProvides examples of models appropriate to the four stages of human-system interaction\u003c\/li\u003e \u003cli\u003eExamines in detail the philosophical underpinnings and assumptions of modeling\u003c\/li\u003e \u003cli\u003eDiscusses how a model fits into doing science and the considerations in garnering evidence and arriving at beliefs for the modeled phenomena\u003c\/li\u003e \u003c\/ul\u003e \u003cp\u003e\u003ci\u003eModeling Human-System Interaction \u003c\/i\u003eis a reference for professionals in industry, academia and government who are researching, designing and implementing human-technology systems in transportation, communication, manufacturing, energy, and health care sectors.\u003c\/p\u003e\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e\u003cp\u003ePreface xi\u003c\/p\u003e \u003cp\u003eIntroduction 1\u003c\/p\u003e \u003cp\u003e\u003cb\u003e1 Knowledge 5\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eGaining New Knowledge 5\u003c\/p\u003e \u003cp\u003eScientific Method: What Is It? 7\u003c\/p\u003e \u003cp\u003eFurther Observations on the Scientific Method 8\u003c\/p\u003e \u003cp\u003eReasoning Logically 10\u003c\/p\u003e \u003cp\u003ePublic (Objective) and Private (Subjective) Knowledge 11\u003c\/p\u003e \u003cp\u003eThe Role of Doubt in Doing Science 11\u003c\/p\u003e \u003cp\u003eEvidence: Its use and Avoidance 12\u003c\/p\u003e \u003cp\u003eMetaphysics and its Relation to Science 12\u003c\/p\u003e \u003cp\u003eObjectivity, Advocacy, and Bias 13\u003c\/p\u003e \u003cp\u003eAnalogy and Metaphor 14\u003c\/p\u003e \u003cp\u003e\u003cb\u003e2 What is a Model? 17\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eDefining “Model” 17\u003c\/p\u003e \u003cp\u003eModel Attributes: A New Taxonomy 20\u003c\/p\u003e \u003cp\u003eExamples of Models in Terms of the Attributes 25\u003c\/p\u003e \u003cp\u003eWhy Make the Effort to Model? 27\u003c\/p\u003e \u003cp\u003eAttribute Considerations in Making Models Useful 27\u003c\/p\u003e \u003cp\u003eSocial Choice 30\u003c\/p\u003e \u003cp\u003eWhat Models are Not 31\u003c\/p\u003e \u003cp\u003e\u003cb\u003e3 Important Distinctions in Modeling 33\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eObjective and Subjective Models 33\u003c\/p\u003e \u003cp\u003eSimple and Complex Models 35\u003c\/p\u003e \u003cp\u003eDescriptive and Prescriptive (Normative) Models 36\u003c\/p\u003e \u003cp\u003eStatic and Dynamic Models 36\u003c\/p\u003e \u003cp\u003eDeterministic and Probabilistic Models 36\u003c\/p\u003e \u003cp\u003eHierarchy of Abstraction 37\u003c\/p\u003e \u003cp\u003eSome Philosophical Perspectives 38\u003c\/p\u003e \u003cp\u003e\u003cb\u003e4 Forms of Representation 41\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eVerbal Models 41\u003c\/p\u003e \u003cp\u003eGraphs 42\u003c\/p\u003e \u003cp\u003eMaps 44\u003c\/p\u003e \u003cp\u003eSchematic Diagrams 45\u003c\/p\u003e \u003cp\u003eLogic Diagrams 46\u003c\/p\u003e \u003cp\u003eCrisp Versus Fuzzy Logic (see also Appendix, Section “Mathematics of Fuzzy Logic”) 48\u003c\/p\u003e \u003cp\u003eSymbolic Statements and Statistical Inference (see also Appendix, Section “Mathematics of Statistical Inference From Evidence”) 50\u003c\/p\u003e \u003cp\u003e\u003cb\u003e5 Acquiring Information 51\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eInformation Communication (see also Appendix, Section “Mathematics of Information Communication”) 51\u003c\/p\u003e \u003cp\u003eInformation Value (see also Appendix, Section “Mathematics of Information Value”) 53\u003c\/p\u003e \u003cp\u003eLogarithmic‐Like Psychophysical Scales 54\u003c\/p\u003e \u003cp\u003ePerception Process (see also Appendix, Section “Mathematics of the Brunswik\/Kirlik Perception Model”) 54\u003c\/p\u003e \u003cp\u003eAttention 55\u003c\/p\u003e \u003cp\u003eVisual Sampling (see also Appendix, Section “Mathematics of How Often to Sample”) 56\u003c\/p\u003e \u003cp\u003eSignal Detection (see also Appendix, Section “Mathematics of Signal Detection”) 58\u003c\/p\u003e \u003cp\u003eSituation Awareness 59\u003c\/p\u003e \u003cp\u003eMental Workload (see also Appendix, Section “Research Questions Concerning Mental Workload”) 60\u003c\/p\u003e \u003cp\u003eExperiencing What is Virtual: New Demands for Human–System Modeling (see also Appendix Section “Behavior Research Issues in Virtual Reality”) 64\u003c\/p\u003e \u003cp\u003e\u003cb\u003e6 Analyzing the Information 69\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eTask Analysis 69\u003c\/p\u003e \u003cp\u003eJudgment Calibration 70\u003c\/p\u003e \u003cp\u003eValuation\/Utility (see also Appendix, Section “Mathematics of Human Judgment of Utility”) 72\u003c\/p\u003e \u003cp\u003eRisk and Resilience 73\u003c\/p\u003e \u003cp\u003eDefinition of Risk 73\u003c\/p\u003e \u003cp\u003eMeaning of Resilience 73\u003c\/p\u003e \u003cp\u003eTrust 75\u003c\/p\u003e \u003cp\u003e\u003cb\u003e7 Deciding on Action 77\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eWhat is Achievable 77\u003c\/p\u003e \u003cp\u003eDecision Under Condition of Certainty (see also Appendix, Section “Mathematics of Decisions Under Certainty”) 78\u003c\/p\u003e \u003cp\u003eDecision Under Condition of Uncertainty (see also Appendix, Section “Mathematics of Decisions Under Uncertainty”) 79\u003c\/p\u003e \u003cp\u003eCompetitive Decisions: Game Models (see also Appendix “Mathematics of Game Models”) 79\u003c\/p\u003e \u003cp\u003eOrder of Subtask Execution 80\u003c\/p\u003e \u003cp\u003e\u003cb\u003e8 Implementing and Evaluating the Action 83\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eTime to Make a Selection 83\u003c\/p\u003e \u003cp\u003eTime to Make an Accurate Movement 84\u003c\/p\u003e \u003cp\u003eContinuous Feedback Control (see also Appendix, Section “Mathematics of Continuous Feedback Control”) 85\u003c\/p\u003e \u003cp\u003eLooking Ahead (Preview Control) (see also Appendix, Section “Mathematics of Preview Control”) 87\u003c\/p\u003e \u003cp\u003eDelayed Feedback 88\u003c\/p\u003e \u003cp\u003eControl by Continuously Updating an Internal Model (see also Appendix, Section “Stepping Through the Kalman Filter System”) 88\u003c\/p\u003e \u003cp\u003eExpectation of Team Response Time 90\u003c\/p\u003e \u003cp\u003eHuman Error 91\u003c\/p\u003e \u003cp\u003e\u003cb\u003e9 Human–Automation Interaction 95\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eHuman–Automation Allocation 95\u003c\/p\u003e \u003cp\u003eSupervisory Control 96\u003c\/p\u003e \u003cp\u003eTrading and Sharing 98\u003c\/p\u003e \u003cp\u003eAdaptive\/Adaptable Control 101\u003c\/p\u003e \u003cp\u003eModel‐Based Failure Detection 102\u003c\/p\u003e \u003cp\u003e\u003cb\u003e10 Mental Models 105\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eWhat is a Mental Model? 105\u003c\/p\u003e \u003cp\u003eBackground of Research on Mental Models 106\u003c\/p\u003e \u003cp\u003eACT‐R 108\u003c\/p\u003e \u003cp\u003eLattice Characterization of a Mental Model 110\u003c\/p\u003e \u003cp\u003eNeuronal Packet Network as a Model of Understanding 112\u003c\/p\u003e \u003cp\u003eModeling of Aircraft Pilot Decision‐Making Under Time Stress 113\u003c\/p\u003e \u003cp\u003eMutual Compatibility of Mental, Display, Control, and Computer Models 114\u003c\/p\u003e \u003cp\u003e\u003cb\u003e11 Can Cognitive Engineering Modeling Contribute to Modeling Large‐Scale Socio‐Technical Systems? 115\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003eBasic Questions 115\u003c\/p\u003e \u003cp\u003eWhat Large‐Scale Social Systems are we Talking About? 116\u003c\/p\u003e \u003cp\u003eWhat Models? 120\u003c\/p\u003e \u003cp\u003ePotential of Feedback Control Modeling of Large‐Scale Societal Systems 122\u003c\/p\u003e \u003cp\u003eThe STAMP Model for Assessing Errors in Large‐Scale Systems 122\u003c\/p\u003e \u003cp\u003ePast World Modeling Efforts 123\u003c\/p\u003e \u003cp\u003eToward Broader Participation 124\u003c\/p\u003e \u003cp\u003eAppendix 129\u003c\/p\u003e \u003cp\u003eMathematics of Fuzzy Logic 129\u003c\/p\u003e \u003cp\u003eMathematics of Statistical Inference from Evidence 131\u003c\/p\u003e \u003cp\u003eMathematics of Information Communication 132\u003c\/p\u003e \u003cp\u003eMathematics of Information Value 134\u003c\/p\u003e \u003cp\u003eMathematics of the Brunswik\/Kirlik Perception Model 135\u003c\/p\u003e \u003cp\u003eMathematics of How Often to Sample 136\u003c\/p\u003e \u003cp\u003eMathematics of Signal Detection 138\u003c\/p\u003e \u003cp\u003eResearch Questions Concerning Mental Workload 141\u003c\/p\u003e \u003cp\u003eBehavior Research Issues in Virtual Reality 144\u003c\/p\u003e \u003cp\u003eMathematics of Human Judgment of Utility 146\u003c\/p\u003e \u003cp\u003eMathematics of Decisions Under Certainty 147\u003c\/p\u003e \u003cp\u003eMathematics of Decisions Under Uncertainty 149\u003c\/p\u003e \u003cp\u003eMathematics of Game Models 150\u003c\/p\u003e \u003cp\u003eMathematics of Continuous Feedback Control 152\u003c\/p\u003e \u003cp\u003eMathematics of Preview Control 153\u003c\/p\u003e \u003cp\u003eStepping Through the Kalman Filter System 154\u003c\/p\u003e \u003cp\u003eReferences 159\u003c\/p\u003e \u003cp\u003eIndex 167\u003c\/p\u003e","brand":"John Wiley \u0026 Sons Inc","offers":[{"title":"Default Title","offer_id":49407025348951,"sku":"9781119275268","price":86.36,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9781119275268.jpg?v=1730497914","url":"https:\/\/bookcurl.com\/products\/modeling-humansystem-interaction-9781119275268","provider":"Book Curl","version":"1.0","type":"link"}