We think you have liked this presentation. If you wish to download it, please recommend it to your friends in any social system. Share buttons are a little bit lower. Thank you!
Presentation is loading. Please wait.
Published byStanley Hinchcliff
Modified over 3 years ago
Human-Machine InteractionMICA R&D Project Human-Machine Interaction / Interazione Uomo-Machina/ by Adam Maria Gadomski URL: ENEA, C.R.Casaccia 18 November 1999 ? On the rights of the web white paper (Intell.Prop.) - © ENEA, A.M.Gadomski, 1999.
Presentation outline MICA ProjectHuman-Machine Interaction from the Systemic and Cognitive Perspective Contribution to the MICA Task D: Realization of an Integrated Modeling Environment for the Hardware/Software/Human Components of Plant Control Room Systems : Study on a Meta-Modeling Frameworks. Presentation outline Problem Recognition Problem Identification Possible Solutions Conclusions "Make everything as simple as possible, but not simpler.” [Albert Einstein] © ENEA, A.M.Gadomski,
Preface MICA Project Human-Machine Interaction Methodology ResultsThis my activity have been focused on a preliminary study of the human mental errors of industrial operators involved in the control and supervisory of high-risk complex technological systems. It deals with the identification of human mental errors and possibilities of their mitigation through an application of intelligent computer decision support systems. Methodology Heuristic application of the TOGA (Top-down Object-based Goal-oriented Approach) methodology to the problem identification. Application of the IPK conceptual framework to the cognitive operator modelling [http://erg4146.casaccia.enea.it/]. Results An indication and the preliminary analysis of mental functins and tasks which could be supported or executed by IDSSs (Intelligent Computer Decision Support Systems). Problem Recognition Problem Identification Possible Solutions Conclusions Dec.97, © ENEA, A.M.Gadomski,
Problem Recognition MICA Project Human-Machine InteractionHuman-Machine Interaction is a continuously growing domain of interest of researchers and practictioners. It is a consequence of ever more and more complex technologies and systems controlled and managed by humans. The problem is dedected from the perspectives of : - efficacy and quality of the production - economy and sostenibility , and especially, - safety and reliability of human component in human-machine aggregates. Problem Recognition Problem Identification Possible Solutions Conclusions © ENEA, A.M.Gadomski,
Problem Recognition MICA Project Human-Machine InteractionThe research in the field of Human-Machine Interaction (AltaVista: doc. ) is also distributed among such domains as: Man-Machine Interface AltaVista: doc. Human-Computer Interface - AltaVista: 2868 doc. Lycos: doc. Stanford: 524 MIT: Human-Computer Communication -AV. 734 Human-Computer Cooperation AV. 39 Cognitive Technology AV. 985 Cognitive Engineering AV. 3015 Problem Recognition Problem Identification Possible solutions Conclusions © ENEA, A.M.Gadomski,
Problem Recognition MICA ProjectHuman-Machine Interaction MICA Project Problem Recognition Classical engineering paradign: To addopt humans to machine failured in the case of high-risk systems and complex tasks. Problem Recognition Problem Identification Possible solutions Conclusions ...is a classical example of the consequences of a badly designed user interface [Excerpt from the official report to the Three Mile Island nuclear accident] New systemic perspective:” a joint human machine system is performing the task” [E.Hollnagel at al, 94], “Human ignorance is a source of defeates and... human power” © ENEA, A.M.Gadomski,
Problem Recognition MICA Project Human-Machine InteractionPoorly designed user interface causes economical loss: - rejection , - rare using. Badly designed user interface causes catastrofic human errors trough: > confusion, misleading presentation of information, -> misinterpretation, -> cause of dangerous actions. More difficult is to specify what should be implemented than how to do it. We need appropriate goal-oriented models Goal: make communication smoothest possible to interfere least possible with thought process. [W.Joerg, Alberta Univ.95] Problem Recognition Problem Identification Possible solutions Conclusions © ENEA, A.M.Gadomski,
Problem Recognition MICA ProjectHuman-Machine Interaction MICA Project Problem Recognition "The goal is to create software that works ---really works --- in being appropriate and effective for people who live in the world that the software creates.” [Terry Winograd, HCI,96, and yet: Problem Recognition State of the Art Problem Identification Possible Solutions Conclusions Human-Machine Interaction should be modeled from the human and systemic perspective but not invented by software specialists. [KMC, E.Swanstrom,1997] © ENEA, A.M.Gadomski,
Problem Identification approchesMICA Project Human-Machine Interaction Problem Identification approches Sistemic Approach Cognitivistic Approach Human - Machine Interactions Problem Recognition Problem Identification Possible solutions Conclusions Software + Hardware Systems Software Technologies & Engineering Platform © ENEA, A.M.Gadomski,
MICA Project Systemic Perspective on Reliability and Safety ofHuman-Machine Interaction Systemic Perspective on Reliability and Safety of Human-Machine Interactions (HMI) HMI can be seen as a process. Reliability and Safety can be seen as a two complex properties of HMI and characterized by integrated generalized indicators: Reliability Indicator - R Safety Indicator - Sf The carrier of the HMI process is the coupled system: Human-Machine. Problem Recognition Problem Identification Possible solutions Conclusions © ENEA, A.M.Gadomski,
Problem IdentificationMICA Project Human-Machine Interaction Systemic Perspective Cognitivistic Perspective Technological Perspective Problem Identification Modeling Design Soft-Tools develop. Systemic Perspective Cognitivistic Perspective Technological Perspective Problem Recognition Problem Identification Possible Solutions Conclusions © ENEA, A.M.Gadomski,
Elementary heterogenious unit in the modern systemic approach [Gad.99]MICA Project Human-Machine Interaction Systemic Perspective Top-down identification and decomposition rules Systemic Perspective Cognitivistic Perspective Technological Perspective H CSS HO ENV AD Problem Recognition Problem Identification Possible solutions Conclusions Elementary heterogenious unit in the modern systemic approach [Gad.99] H - Human, CSS - Computer Support Systems (Web) HO - Human Organization AD - Domain of Activity ENV - Environment © ENEA, A.M.Gadomski,
MICA Project Human-Machine Interaction Systemic PerspectiveGiven: Objectives, Functions and their indicators Systemic Perspective Everything said is said by an observer' (Maturana & Varela, 1980) Identification of Systems involved Identification of Processes, Activities and their attributes Search expressions (models) of the type: indicators (attributes) Search attributes which min or max of indicators [Heuristic Appication of SPG, Gadomski,since 86;99] Problem Recognition Problem Identification Possible solutions Conclusions Modification/design of Processes and Systems according to selected attributes Software engineer © ENEA, A.M.Gadomski,
? MICA Project Systemic Perspective Human-Machine InteractionKey Factor: RISK Risk Analysis Risk Sources Human Errors Application Domains: # HOME WORKS # PUBLIC SERVICIES # ADMINISTRATION # CULTURE # INDUSTRY # HEALTH # MILITARY # INSTRUCTION & SCIENCE High Risk Domains ? Problem Recognition Problem Identification Possible Solutions Conclusions © ENEA, A.M.Gadomski,
Machine (controlled system/processes)Human-Machine Interaction MICA Project Systemic Perspective Physical environment Causes of Human Errors MIND Organization Machine (controlled system/processes) Control and Measurement System Computer Console Human operator Psycho-social environment Hardware & Software Problem Recognition Problem Identification Possible solutions Conclusions © ENEA, A.M.Gadomski,
Bases of the Cognitivistic PerspectiveHuman-Machine Interaction MICA Project Bases of the Cognitivistic Perspective "the study of intelligence and intelligent systems, with particular reference to intelligent behaviour as computation" (Simon, H. A. & C. A. Kaplan, "Foundations of cognitive science", in Posner, M.I.T. 1989 “Cognitive science is a multidisciplinary approach to the study of the human mind.” Kalish, P.N.Johnson-Lard-Mental Models,83. M.Olivetti-Belardinelli - Mental Architectures,98, A.Slomans - Emotional Agents. John Locke's (1690). Essay Concerning Human Understanding and the nature of human consciousness -First model.. Professor Norman, the first chair of the UCSD Department of Cognitive Science, originated the Cognitive Engineering course. Distributed Cognition and Human Computer Interaction Laboratory. Univ. of California.,May 99. Problem Recognition Problem Identification Possible solutions Conclusions © ENEA, A.M.Gadomski,
Cognitive Engineering PerspectiveHuman-Machine Interaction MICA Project Cognitive Engineering Perspective the principles of cognitive engineering refers to: user-centered design ( its practices have wide applicability) and human-computer interaction in particular. It is base on cognitive models. Human-computer interaction (HCI) is the intersection between the social and cognitive sciences, on the one hand, and computer science and technology, on the other. HCI researchers analyze and design interaction technologies (e.g., displays and pointing devices, gestures and sketching). They study and improve the processes of technology development (e.g., usability evaluation, software toolkits, cognitive ethnography). Over the past two decades, HCI has progressively integrated scientific concerns with the engineering goal of improving the usability of computers. established a body of technical knowledge and methodology, and contributed broadly to the development of new computer technologies and applications. See also: MIT Encyclopedia of Cognitive Science. Problem Recognition Problem Identification Possible solutions Conclusions © ENEA, A.M.Gadomski,
Cognitive Technology PerspectiveHuman-Machine Interaction MICA Project Cognitive Technology Perspective Douglas Hofstadter is College Professor of cognitive science and computer science, director of the Center for Research on Concepts and Cognition, Ph.D. in physics, University of Oregon, 1975; Pulitzer Prize. The First International Conference on Cognitive Technology (Hong Kong, 1995) stressed the need for a radically new way of thinking about the impact computer technology has on humans, especially on the human mind. Our main aim at that time was a consideration of these effects with respect to rendering the interface between people and computers more humane. Cognitive technologies in Europe: Rasmunssen, Andeson - Riso National Lab Hollnagel - Halden Project (from about 18 years) Gadomski (since 86), Nanni (87), Balducelli (93), DiCostanzo - ENEA . Problem Recognition Problem Identification Possible solutions Conclusions © ENEA, A.M.Gadomski,
General Cognitivistic PerspectiveHuman-Machine Interaction MICA Project General Cognitivistic Perspective Systemic + Psychology + Physics Mindware applied to the identification of mental processes of humans and living systems Development of the Universal Theory of Cognition Applied to living systems Applied to autonomous H/Software systems Problem Recognition Problem Identification Possible solutions Conclusions Applied to Human-Machine Interaction Software Engineering Platform © ENEA, A.M.Gadomski,
Cognitivistic PerspectiveHuman-Machine Interaction MICA Project “The web is constructed for the communication between humans not computers” Cognitivistic Perspective Risk Human Errors Human Models Levels of a Human Functional Model: Sensorial & Manipulation Perception Reasoning Decision-Making Communication CognitiveModeling Problem Recognition Problem Identification Possible solutions Conclusions © ENEA, A.M.Gadomski,
Possible Solutions MICA ProjectHuman-Machine Interaction MICA Project Possible Solutions Existing Strategies for improving of HMI - Command-driven - improving what is requested Event-driven - post-accident improvement Means-driven - improv. based on available know-how Goal-driven (Model-driven) - research based eng. improv. Problem Recognition Problem Identification Possible solutions Conclusions © ENEA, A.M.Gadomski,
Possible Solutions SearchingHuman-Machine Interaction MICA Project Possible Solutions Searching Assumptions: 1. Every human interaction with complex machine is through computer then a Human-Computer Cooperation is needed. 2. Every human interaction with complex machine is decomposable on decision-making mental events. Mental processes Machine + Computer processes . . . ? Problem Recognition Problem Identification Possible solutions Conclusions © ENEA, A.M.Gadomski,
? Possible Solutions MICA Project Mental processes . . .Human-Machine Interaction MICA Project Possible Solutions Mental processes ? . . . Machine + Computer processes Computer substitutes or supports goal-dependent tasks of human user/operator. Critical points (recognizable events) which need to be identified by the cognitive modeling. Problem Recognition Problem Identification Possible solutions Conclusions © ENEA, A.M.Gadomski,
We need intelligent agents.Human-Machine Interaction MICA Project Possible Solutions Solution: In order to increase human reliability and safety in high-risk complex human-machine systems, we need to shift mental functions from human to computer, to construct computer ever more intelligent. Is it my idea ? We need intelligent agents. ESPECIALLY FOR NOT ROUTINE, MULTI-DATA TASKS UNDER TIME CONSTRAINS. Problem Recognition Problem Identification Possible solutions Conclusions © ENEA, A.M.Gadomski,
Possible Solutions: an Abstract Intelligent Agent, AIAHuman-Machine Interaction MICA Project Possible Solutions: an Abstract Intelligent Agent, AIA Two roles of AIA: 1. user model -- cognitive intelligent agent 2. kernel of a computer intelligent assisstant. Intelligent - an agent with capability to the modification of own preferences, capability of learning and meta-reasoning.[TOGA,Gadomski]. Emotional agent - Modeling of emotions, emotional behaviour [Web] Problem Recognition Problem Identification Possible solutions Conclusions © ENEA, A.M.Gadomski,
Possible Solutions: Project ResultsHuman-Machine Interaction MICA Project Possible Solutions: Project Results 1. Recognized utility of the TOGA meta-theory [Gadomski,90,99] and SPG conceptualization [Gadomski,86,99] to the goal-oriented knowledge ordering in meta-system engineering applied to the analysis of HMI attributes. 2. Recognized plausibility of the identification of human mental states by the Protocol Analysis [K.A.Ericsson, H.A.Simon] applied to the IPK cognitive architecture [A.M.Gadomski,98,99]. 3. Formal conceptual separation of knowledge, preferences and information acquisition in Human-Machine Interactions [Gadomski at al.,99]; has been applied to the IDA-MICA Project. Problem Recognition Problem Identification Possible solutions Conclusions © ENEA, A.M.Gadomski,
Conclusions MICA Project Human-Machine InteractionThe work has been supported by the Scientific Cooperaton (ortogonal no profits activity) with The Interuniversity Center for the Research on Cognitive Processing in Natural and Artificial Systems ( ECONA). Gadomski, Pestilli :INTELLIGENT DECISION SUPPORT SYSTEM: TOGA COGNITIVE AGENT, in frame of The ECONA’s Meeting on “ Research Activities on Cognitive Modeling, May ,99 [Web]. A.M.Gadomski,S. Ceccacci:Seminar ”Contesto TOGA per la Progettazione di un Agente Intelligente Astratto ed il suo Decision-Making” , Perugia,99 [Web](Bora per Tesi di L.) A.M.Gadomski: TOWARDS SYSTEM ENGINEERING & TECHNOLOGIES, SET, transparent-sheet, ENEA, 99[Web]. The obtained resualts are also the base for the proposal of a research project for the FET * Open (5th Program EU) with Univ. of Brussel,Poland, Ansaldo, ECONA (under preparation). *FET - Future and Emerging Technologies © ENEA, A.M.Gadomski,
One or More Topologies ? One or More Topologies ? A methodological reflection IRRIIS Project, WP2.1 “Topology Analysis” Rome Meeting, 6,7 April 2006 IST.
EIDA Project ( Proposal ) Research and Technical Background Emergency Intelligent Decision Assistant: Emergency Intelligent Decision Assistant: Toolkit.
A-MAZE NEST-IDEA Seminar "Interdisciplinarity in Research" 22nd, June 2004 Applied Mathematics Ability Zone Adam Maria Gadomski (ENEAs contribution ) Towards.
Cognitive Science and Biomedical Informatics Department of Computer Sciences ALMAAREFA COLLEGES.
Universal Top SYNTEX Functional Architecture Building Working Document Adam Maria Gadomski, Vittorio Rosato ENEA A Contribution to the SYNTEX Development.
Development of Indicators for Integrated System Validation Leena Norros & Maaria Nuutinen & Paula Savioja VTT Industrial Systems: Work, Organisation and.
Managerial Intelligent Node for Decisional Emergency Support Energy Department Strategic Project Balducelli Claudio Bologna Sandro Gadomski Adam M. More.
Riga Technical University Department of System Theory and Design Usage of Multi-Agent Paradigm in Multi-Robot Systems Integration Assistant professor Egons.
1. Human – the end-user of a program – the others in the organization Computer – the machine the program runs on – often split between clients & servers.
Pat Langley Computational Learning Laboratory Center for the Study of Language and Information Stanford University, Stanford, California USA
Ecological Interface Design https://publicwiki.deltares.nl/display/BWN/Tool+-+Interactive+Dredge+Planning+Tool+Singapore.
HCI Meeting 1 Thursday, August 26. Class Activities  Student questionnaire Answer the following questions: 1.When and where was the computer mouse.
1 User-Centric The Human Factor in Design Susanne M. Furman, PhD Usability Engineer Web Communication and New Media Division U.S. Department of Health.
Rule Engine for executing and deploying the SAGE-based Guidelines Jeong Ah Kim', Sun Tae Kim 2 ' Computer Education Department, Kwandong University, KOREA.
© Yilmaz “Agent-Directed Simulation – Course Outline” 1 Course Outline Dr. Levent Yilmaz M&SNet: Auburn M&S Laboratory Computer Science &
Sub-Project III 4: CRESCO-SOC-COG Second Progress Report (15 February June 2007)
Keynote paper: Unlocking the learning value of wireless mobile devices Adviser: Ming-Puu Chen Presenter: Li-Chun Wang Roschelle, J. (2003). Keynote paper:
Knowledge representation https://store.theartofservice.com/the-knowledge-representation-toolkit.html.
Top-Down Incremental Development of Agents' Architecture for Emergency Management Systems: Management Systems: TOGA methodology HID, CAMO Seminars Series.
© 2017 SlidePlayer.com Inc. All rights reserved.