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THE “DIGITAL FRIEND”: DESIGN FEATURES OF A PSYCHOLOGICAL SUPPORT SYSTEM FOR SPACE-CREWS

H.-J. Hoermann1, B. Johannes1, V.P. Salnitski2 & Y. Pecena1

German Aerospace Center (DLR), Institute of Aerospace Medicine Institute for Biomedical Problems (IBMP), Moscow/Russia

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Hoermann et al., „Digital Friend“, 16th IAA Humans in Space Symposium, Beijing, 20-24 May 2007

What is the „Digital Friend“? Extension of an existing psycho-physiological monitoring and advisory system, Neurolab-2000 Knowledge-based system, using ontologies from medicine, physiology, individual and group psychology domains Adaptive tracking and analysing of system parameters, including human, environment, technology, and mission Serves the crew and the individuals by functioning as a private coach as well as a synthetic crew-member

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Long Duration Space Exploration Missions – Psychological and Operational Issues Unprecedented experiences have to be mentally „digested“ Feeling having no return option („Away from home in a can“; Pawelczyk) Maladaptation (Space Adaptation Syndrome), isolation Daily work routine may affect crew morale and efficiency Social and perceptual deprivation Communication constraints Demanding work program Solving unforeseen problems for which crew has not been trained No re-supply from earth possible Self-sustainability leads to increasing task variety and complexity Reduced number of layers of authority for operational decisions Example Mars exploration: On the human side this requires attention to health, safety, performance and other attributes of a productive crew in order to prevent risks to mission success. Once committed to leave the orbit, crew will need to rely on their own skills and training and specialized support systems to manage the mission challenges.

(ref.: since 1966: IBMP; Hoffman & Kaplan, 1997; HUMEX-Study, ESA 2003)

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History of Electronic Support Tools ELIZA – Early AI chatterbot acts as synthetic therapist (MIT, 1965) FICTION: HAL, R2D2, C3PO, DATA 7 MIT/NASA Astronaut Science Advisor (PI-In-A-Box, 1993) NASA: CLARISSA a voice operated procedure assistant, deployed to ISS 2005 HONEYWELL: Intelligent Astronaut Associate (2005) TNO/NL: ALICE interactive diary (2007)

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Concept

Goal: Create tools for computer augmented teamwork

Approach: Concept driven not technology driven design Methods: Applying knowledge management techniques to generate an intelligent multi-agent system, which refer to enabling software technologies such as CommonKADS, multi-agent systems, data-mining and machine learning pays attention to system, mission, individual and crew parameters through multiple sensor systems has access to knowledge bases and databases of other systems has reasoning as well as natural language capabilities interacts with crew on demand and autonomous up to a level determined by the user does not have control or moving abilities Should follow the „pleasure principle“ Slide 5


Generic Architecture

Knowledge Engineering and Management: The CommonKADS Methodology (2000) by G. Schreiber, H. Akkermans, A. Anjewierden, R. De Hoog, N. Shadbolt, W. Van De Velde & B. Wielinga. MIT Press. ISBN 0-262-19300-0. ESPRIT: http://cordis.europa.eu/esprit/home.html Slide 6


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Levels of Analysis and Design

CommonKADS Website at Universiteit van Amsterdam

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Methodologies at Work Knowledge Design Data Mining

MAS

Machine Learning

Knowledge Analysis & Design Methodologies like CommonKADS (Esprit IT), Representations and representational like Web Ontology Language (OWL), Protegé2000 (Stanford-University), CmapTools Data Mining • Decision Trees and Rules • Nonlinear Regression and Classification Methods • Example-based Methods • Probabilistic Graphical Dependency Models • Relational Learning Models Multi Agent System (MAS) For example: INGENIAS, AOSE (AgentOriented Software Engineering) Machine Learning • Batch versus Online Learning • Learning from Complete versus Partial Feedback

Knowledge Engineering and Management: The CommonKADS Methodology (2000) by G. Schreiber, H. Akkermans, A. Anjewierden, R. De Hoog, N. Shadbolt, W. Van De Velde & B. Wielinga. MIT Press. ISBN 0-262-19300-0. ESPRIT: http://cordis.europa.eu/esprit/home.html Slide 8


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„Digital Friend“ Certain question: „Is it possible that... ?”

Space

Technology

Medicine

Psychology

Physics Energy Navigation Time

Rocket Survival Systems Computer / Software Procedures

Physiology Biochemistry Molecular Medicine Medical Support

Individual + Group Psychology Psychophysiology Psychological Support

(Typical) Expert answer: „It is possible with 85% probability of success!„ Slide 9


„Digital Friend“ – Sample Ontologies Medicine

Psychology

Physiology Biochemistry Molecular Medicine Medical Support

Individual + Group Psychology Psychophysiology Psychological Support

Common Crewmember and Crew Data / Statistics Mission Specific Data / Conditions Common Knowledge (Models) Task Related Procedures / Regulations / Heuristic Slide 10


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Psychological Screening Database System Behaviour Performance Knowledge Attitudes Personality Aptitudes Biography

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Proposed System Architecture of Digital Friend

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„Digital Friend“ Common Crewmember and Crew Data

Medicine Physiology Biochemistry Moleculare Medicine Medical Support

Medical Anamnesis, Constitution data, Common fitness, Gender, age, weight Daily Medical Morning Check (RR, HR, weight) Specific Medical Investigations (Brain, Neurological, Cardiovascular, Autonomous NS (e.g.. AOT-Assessment), Bones, Muscles, Vestibular, Eyes, etc)

C o u n t e r m e a s u r e s

Monthly Medical Check Slide 13



Psychology Individual

Psycho-physiological anamnesis, school results, educational results, special skills, talents; (Arts, scientific, technical, professional, sportive) Temperament, character, will, personality, Intelligence, self-control / tolerance Daily phone, voice stress analysis, : (as far as not private) Monthly monitoring of •- individual psychological state and workability (cognitive capacity, memory.) •- special individual skills (e.g tele-operated docking and robotic activities) Training and refresher programs (6df) Slide 14


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Psychology

Social anamnesis, cultural roots, social-material roots, participation, role in natural and educational groups (leadership, cooperation), Communication style, professional career

Group

Daily Commander Report

Dynamics

Reports, messages, communications, : (as far as not private) Natural Group Diagnostics (group performances in professional tasks - 6df, housekeeping-monitoring, voice cross analysis, video analysis, sonographical sociogram)

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Potential Friction Due to Different Working Styles (LIFO-Method)

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Folie 15 D37 D38

DLR; 13.03.2007 DLR; 13.03.2007

Common Pitfalls of Automation Automation complacency (always rely on one solution) Automation dependency (choose the easy way, procrustination of problems, diminished problem solving abilities, “enshrined best practices”) “Super-intelligent” locks, undefined states (Hibbard, 2001;Degani, 2005) Integration of KM databases with other applications, possible interference Continuous system integrity (assumptions and rationale must be transparent, solutions subject to regular inquiry and validation)

Task analysis, user involvement, acceptability checks, interface

attractivity, data privacy and system intent transparency to enable beneficial human-automation teamwork Slide 17


Capability Elements

Organize and provide information Capture spacecraft and mission conditions Monitor individual and team states Identify crew and individual intent Personalize its behavior according to user preference Facilitate communications Consult, coach and entertain Augment team decisions Continuously expand system knowledge

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„Is it possible, that ... ?” Space

Technology Medicine Psychology Common Crewmember and Crew Data / Statistics

Mission Specific Data Common Knowledge (Models) Task Related Procedures / Regulations

„It is possible with 85% probability of success!„ Slide 19


Thank You!

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