Teaming with Machines
The role of autonomous systems in
collaborative environments


                                     ...
My name is…

    Martijn Neef
    Networked Organizations Group
    Business Unit Information and Operations
    TNO Defen...
Lecture overview

    • Part I: Teaming with machines
          • On teams, machines and autonomy
          • From automat...
Part I: Teaming with Machines
On teams, machines and autonomy



                                      Martijn Neef
      ...
We are surrounded by machines

    • Our working and living environments are filled with machines,
      systems and netwo...
We are being surrounded by smarter machines

    • Technological developments produce smarter systems
          •   system...
We need a new way of thinking about teams

    • Technology will:
          • become more capable, adaptive and reliable
 ...
team
                                  team
7   Teaming with Machines   ISCRAM Summerschool 2009
Human – Machine teams

    • What is a human – machine team, what is not?
          • what is a team?
          • what mus...
What is a team?

    Defining Characteristics of Teams

    • Two or more individuals           • Specialized member roles...
Teaming with machines

     • humans working together
       with artificial actors




10   Teaming with Machines       I...
11   Teaming with Machines   ISCRAM Summerschool 2009
12   Teaming with Machines   ISCRAM Summerschool 2009
13   Teaming with Machines   ISCRAM Summerschool 2009
14   Teaming with Machines   ISCRAM Summerschool 2009
Human – Machine Teams




15   Teaming with Machines   ISCRAM Summerschool 2009
Human – machine teams




16   Teaming with Machines   ISCRAM Summerschool 2009
‘Man – computer symbiosis’

             Man-computer symbiosis is an expected development in
              cooperative in...
From automation to socio-technical design
     make technology more capable




                make the joint human – mac...
The Substitution Myth

     The Substitution Myth It is a common myth that artefacts can be value neutral in the
       se...
Task division and coordination

     • MABA-MABA: Men Are Better At,
       Machines Are Better At..                      ...
Fitts’ List (1951)
21   Teaming with Machines   ISCRAM Summerschool 2009
Machines are constrained in that:            Machines need people to:
                                                    ...
Levels of automation




                             Parasuraman (2000)

23   Teaming with Machines     ISCRAM Summerscho...
Ten Challenges for Making Automation a "Team Player"
     in Joint Human-Agent Activity
     1.  To be a team player, an a...
Autonomy
     • Autonomy: to have control over own internal state and behaviour
     • Challenge: control the autonomy of ...
Example: Human – Agent – Robot Teams

     • Work from Institute for Human and Machine Cognition
           • Jeffrey Brad...
Part II: Designing Human – Machine teams


Case: Augmented Teams for Security
Missions
                                   ...
Augmented Teams:
     Assembling Smart Sensors, Intelligent Networks and
     Humans into Agile Task Groups



           ...
Augmented Teams

     We are exploring design principles for augmented teams.

     An augmented team consists of a collec...
Design challenges

     Can we come up with a design concept for augmented teams..

           • .. with adaptive role- an...
Design challenges




                             information
        control




             human team                ...
Approach

     • Three main ingredients:

           • Functional model
                 • Provides a functional blueprint...
Functional Model
                          Situation                  Command
                         Awareness          ...
Organizational Model
     • Based on OperA (Virginia Dignum, Utrecht University, NL).
           • framework for the speci...
Social contracts, Interaction contracts
      • Social contracts
            • General agreements that need to be adopted ...
Putting it all together…

                              a) a functional model to structure the general system




        ...
Adaptivity and agility
             Organization levels give means to express adaptive measures

         Level     Change...
Adaptivity and agility
             Approachs allows for gradual introduction of new elements
             For instance: i...
autonomy and
      task allocation
             choices
     between actors
                                    coordinati...
FieldLab Indoor Safety and Security
                                     • Fieldlab Indoor Safety
                        ...
Fieldlab Indoor Safety and Security




41   Teaming with Machines                 ISCRAM Summerschool 2009
Experiments

     • Network built around a service oriented network (RESTlet)
     • Human contracts are still just ‘on pa...
Roles changes




     B




43   Teaming with Machines   ISCRAM Summerschool 2009
Roles changes




     B




44   Teaming with Machines   ISCRAM Summerschool 2009
Roles changes




     B




45   Teaming with Machines   ISCRAM Summerschool 2009
Some observations

     • Observations
           • Using organizational models and contracts seems worthwhile to
        ...
Concerns

     • Design concerns

           •   Define who is responsible for role and task allocation
           •   Set...
VIS
     Scenario 2009
                                             B            B                  B

                   ...
Further developments

     Current developments:
     • Further formalize interaction contracts and contract management,
 ...
Part III: Implications and Discussion
Points to ponder



                                          Martijn Neef
         ...
Implications

     • Machine teaming is not the stuff of science-fiction movies. It’s
       already here.. even though in...
Discussion



     • Do you have any personal experiences (good or bad) with
       technology that resemble man – machine...
53   Teaming with Machines   ISCRAM Summerschool 2009
thank you for your attention!




54   Teaming with Machines                      ISCRAM Summerschool 2009
References (relevant own)

     • Neef, Martijn (2006), A Taxonomy of Human - Agent Team Collaborations. In
       Proceed...
References (others)

     • Salas, E., Dickinson, T. L., Converse, S. A., and Tannenbaum, S. I. (1992),
       Toward an u...
References

     • Hollnagel, E. & Woods, D. D. (2005). Joint cognitive systems: Foundations of
       cognitive systems e...
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ISCRAM Summerschool 2009 Lecture - Teaming With Machines (Martijn Neef)

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ISCRAM Summerschool 2009 Lecture (27 August 2009). Teaming with Machines: the role of autonomous systems in collaborative environments

In this talk, we will discuss the implications of autonomous systems on the design of future crisis management teams, with a specific attention to task delegation, role adjustment, responsibility and adaptive autonomy between human and artificial actors. We will discuss why system autonomy is such an important issue and how it affects function allocation between man and machine. We will go over different approaches to teaming with intelligent systems, and relate it to crucial subjects such as decision making, accountability and control. We will present some of our own work on hybrid teams in safety scenarios, and discuss some of our practical experiences.

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ISCRAM Summerschool 2009 Lecture - Teaming With Machines (Martijn Neef)

  1. 1. Teaming with Machines The role of autonomous systems in collaborative environments Martijn Neef TNO Defence, Safety and Security
  2. 2. My name is… Martijn Neef Networked Organizations Group Business Unit Information and Operations TNO Defence, Security and Safety The Hague, The Netherlands e-mail: martijn.neef@tno.nl • Artificial Intelligence • Collaborative Decision Making • Networked Organisations • Human – Machine Systems 1 Teaming with Machines ISCRAM Summerschool 2009
  3. 3. Lecture overview • Part I: Teaming with machines • On teams, machines and autonomy • From automation to joint cognitive system design • Part II: Designing Human – Machine teams • Case study: Augmented Team design, • A practical example from our work at TNO Safety and Security • Part III: Implications and Discussion • Summary and implications • Points to ponder 2 Teaming with Machines ISCRAM Summerschool 2009
  4. 4. Part I: Teaming with Machines On teams, machines and autonomy Martijn Neef TNO Defence, Safety and Security
  5. 5. We are surrounded by machines • Our working and living environments are filled with machines, systems and networks • communication devices, computers, sensors, networks, information sources, actuators, displays, and so on… • we are connected with and dependent on humans and machines in many ways.. 4 Teaming with Machines ISCRAM Summerschool 2009
  6. 6. We are being surrounded by smarter machines • Technological developments produce smarter systems • systems that exhibit smart behaviours • new response options through smart coupling of capabilities • more prominent and active role for intelligent, autonomous systems • artificial systems are being granted more autonomy. • Lots of examples in security, safety and space • robots and unmanned vehicles • information management systems and intelligent agents • traffic management systems • safety and self-defense systems 5 Teaming with Machines ISCRAM Summerschool 2009
  7. 7. We need a new way of thinking about teams • Technology will: • become more capable, adaptive and reliable • be given more autonomy to define their own behaviour • Increase of system autonomy leads to different ways of working with machines: • technology role goes from supplement to active participant • task groups will gradually develop into hybrid teams • we need for a new understanding of the dynamics of hybrid teams task allocation between man and machine interaction patterns between man and machine coordination and communication authorization and responsibility… 6 Teaming with Machines ISCRAM Summerschool 2009
  8. 8. team team 7 Teaming with Machines ISCRAM Summerschool 2009
  9. 9. Human – Machine teams • What is a human – machine team, what is not? • what is a team? • what must an artificial system be capable of? • what are the features and implications of a human – machine team? • Why is this an important area of research? • we need new capabilities to face modern challenges • we need to learn to work together with advanced systems • tight collaboration between humans and machines yields operational benefits… complement each other’s strengths and weaknesses. 8 Teaming with Machines ISCRAM Summerschool 2009
  10. 10. What is a team? Defining Characteristics of Teams • Two or more individuals • Specialized member roles and • Multiple information sources responsibilities • Meaningful task • Task-relevant knowledge interdependencies • Intensive communication • Coordination among members • Adaptive mechanisms • Common, valued goals • Hierarchically organized (Salas, 1995) requires a lot of mutual understanding requires a common grounding requires training and trust usually only used for human teams 9 Teaming with Machines ISCRAM Summerschool 2009
  11. 11. Teaming with machines • humans working together with artificial actors 10 Teaming with Machines ISCRAM Summerschool 2009
  12. 12. 11 Teaming with Machines ISCRAM Summerschool 2009
  13. 13. 12 Teaming with Machines ISCRAM Summerschool 2009
  14. 14. 13 Teaming with Machines ISCRAM Summerschool 2009
  15. 15. 14 Teaming with Machines ISCRAM Summerschool 2009
  16. 16. Human – Machine Teams 15 Teaming with Machines ISCRAM Summerschool 2009
  17. 17. Human – machine teams 16 Teaming with Machines ISCRAM Summerschool 2009
  18. 18. ‘Man – computer symbiosis’ Man-computer symbiosis is an expected development in cooperative interaction between men and electronic computers. It will involve very close coupling between the human and the electronic members of the partnership. The main aims are 1) to let computers facilitate formulative thinking as they now facilitate the solution of formulated problems, and 2) to enable men and computers to cooperate in making decisions and controlling complex situations without inflexible dependence on predetermined programs. J.C.R. Licklider (1915-1990), Man-Computer Symbiosis IRE Transactions on Human Factors in Electronics, volume HFE-1, pages 4-11, March 1960 17 Teaming with Machines ISCRAM Summerschool 2009
  19. 19. From automation to socio-technical design make technology more capable make the joint human – machine team Based on Chalmers (2001) more capable 18 Teaming with Machines ISCRAM Summerschool 2009
  20. 20. The Substitution Myth The Substitution Myth It is a common myth that artefacts can be value neutral in the sense that the introduction of an artefact into a system only has the intended and no unintended effects. The basis for this myth is the concept of interchangeability as used in the production industry, and as it was the basis for mass production – even before Henry Ford. Thus if we have a number of identical parts, we can replace one part by another without any adverse effects, i.e. without any side- effects. … While this in practice holds for simple artefacts, on the level of nuts and bolts, it does not hold for complex artefacts. A complex artefact, which is active rather than passive, ie, one that requires some kind of interaction either with other artefacts or subsystems, is never value neutral. In other words, introducing such an artefact in a system will cause changes that may go beyond what was intended and be unwanted Joint cognitive systems: foundations of cognitive systems engineering, Erik Hollnagel, David D. Woods. 19 Teaming with Machines ISCRAM Summerschool 2009
  21. 21. Task division and coordination • MABA-MABA: Men Are Better At, Machines Are Better At.. typical human knowledge intensiveness tasks • Task division steers coordination. • Coordination renders tasks. collaborative • Challenge: find types of tasks that tasks are suitable for each actor, and designate tasks that can be typical agent performed by more than one. tasks system tasks 20 Teaming with Machines ISCRAM Summerschool 2009
  22. 22. Fitts’ List (1951) 21 Teaming with Machines ISCRAM Summerschool 2009
  23. 23. Machines are constrained in that: Machines need people to: Un-Fitts’ list Sensitivity to context is low and is Keep them aligned to context. Hoffman (2002) ontology-limited. Sensitivity to change is low and Keep them stable given the recognition of anomaly is ontology- variability and change inherent limited. in the world. Adaptability to change is low and is Repair their ontologies. ontology-limited. They are not ‘aware’ of the fact that Keep the model aligned with the the model of the world is itself in the world. world. People are not limited in that: Yet people create machines to: Sensitivity to context is high and Help them stay informed of is knowledge- and attention-driven. ongoing events. Sensitivity to change is high Help them align and repair their and is driven by the recognition perceptions because they rely on of anomaly. mediated stimuli. Adaptability to change is high and Effect positive change following is goal-driven. situation change. They are aware of the fact that the Computationally instantiate their model of the world is itself in the world. models of the world. 22 Teaming with Machines ISCRAM Summerschool 2009
  24. 24. Levels of automation Parasuraman (2000) 23 Teaming with Machines ISCRAM Summerschool 2009
  25. 25. Ten Challenges for Making Automation a "Team Player" in Joint Human-Agent Activity 1. To be a team player, an agent must fulfil the requirements of a Basic Compact to engage in common grounding activities 2. To be an effective team player, agents must be able to adequately model the other participant’s intents and actions vis-à-vis the state and evolution of the joint activity – e.g. are they having trouble? Are they on a standard path proceeding smoothly? What impasses have arisen? How have others adapted to disruptions in the plan? 3. Human-agent team members must be mutually predictable 4. Agents must be directable 5. Agents must be able to make pertinent aspects of their status and intentions obvious to their team-mates 6. Agents must be able to observe and interpret signals of status and intentions. 7. Agents must be able to engage in goal negotiations 8. Support technology for planning and autonomy must enable a collaborative approach 9. Agents must be able to participate in the management of attention 10. All team members muist help control the costs of coordinated activity Klein (2004) 24 Teaming with Machines ISCRAM Summerschool 2009
  26. 26. Autonomy • Autonomy: to have control over own internal state and behaviour • Challenge: control the autonomy of autonomous systems (Bradshaw, 2003) 25 Teaming with Machines ISCRAM Summerschool 2009
  27. 27. Example: Human – Agent – Robot Teams • Work from Institute for Human and Machine Cognition • Jeffrey Bradshaw • Demonstrate the feasibility of a human – machine team for a security task – intruder detection and apprehension by a team of humans and robots. • Smart use of agreements and coordination support to optimize joint performance. • (movie of HART in action) 26 Teaming with Machines ISCRAM Summerschool 2009
  28. 28. Part II: Designing Human – Machine teams Case: Augmented Teams for Security Missions Martijn Neef TNO Defence, Safety and Security
  29. 29. Augmented Teams: Assembling Smart Sensors, Intelligent Networks and Humans into Agile Task Groups Martijn Neef Networked Organizations Group Business Unit Information and Operations TNO Defence, Security and Safety The Hague, The Netherlands Martin van Rijn – Distributed Sensor Systems Group Jan Willem Marck – Distributed Sensor Systems Group Danielle Keus – Modelling, Simulation and Gaming Group 28 Teaming with Machines ISCRAM Summerschool 2009
  30. 30. Augmented Teams We are exploring design principles for augmented teams. An augmented team consists of a collective of sensors, actuators, information processing systems and humans • that are interconnected by a intelligent network • that collaborate in a close and adaptive fashion, and • that, by presence of the artificial actors, augment the capabilities of the human actors alone. 29 Teaming with Machines ISCRAM Summerschool 2009
  31. 31. Design challenges Can we come up with a design concept for augmented teams.. • .. with adaptive role- and tasking capabilities between human and artificial actors • Essential for agility and resilience. The team must be able to cope with changing circumstances, e.g. by changing the behaviour or structure of the organization. • .. that is suitable for the current and future state of technology • Prevent technology bias. Limit the influence of the current state or technology on the approach as much as possible. 30 Teaming with Machines ISCRAM Summerschool 2009
  32. 32. Design challenges information control human team hybrid team with self organising with sensor network clear divison of labour adaptive team Basic challenges • It must be possible to change the organization structure • The team must be configurable at run-time • All elements must be network-connected • Actors must be able to represent themselves • The information flow must self-organize 31 Teaming with Machines ISCRAM Summerschool 2009
  33. 33. Approach • Three main ingredients: • Functional model • Provides a functional blueprint for augmented teams • Organization modeling framework • Provides means to structure interactions and responsibilities • Social and interaction contracts • Provides a way to specify community rules and collaboration demands 32 Teaming with Machines ISCRAM Summerschool 2009
  34. 34. Functional Model Situation Command Awareness & Control • Networked Adaptive Interactive Hybrid Systems model (NAIHS) Level 3 Impact Impact • Blueprint for networked cognitive assessment management systems, grounded in the JDL Situation Situation model Level 2 assessment management • Elements fulfill functional components. Level 1 Object Object assessment management • Three steering dimensions: Signal Signal Level 0 assessment management • level of information abstraction • timescale of effects Physical Data • physical structure Actions Level collection Environment 33 Teaming with Machines ISCRAM Summerschool 2009
  35. 35. Organizational Model • Based on OperA (Virginia Dignum, Utrecht University, NL). • framework for the specification of multi-agent organizations • uses a formal specification language 34 Teaming with Machines ISCRAM Summerschool 2009
  36. 36. Social contracts, Interaction contracts • Social contracts • General agreements that need to be adopted to become part of the organization (job contracts) • organizational aspects (norms and policies, coordination scheme, organization structure) • social rules, administrative rules, communication language … • Interaction contracts • collaborative agreements between actors per task • interaction behaviour (relation between parties, task division) • format and conditions 35 Teaming with Machines ISCRAM Summerschool 2009
  37. 37. Putting it all together… a) a functional model to structure the general system b) three levels of abstraction to represent dependencies and interactions c) social and interaction contracts to put the organization into practice 36 Teaming with Machines ISCRAM Summerschool 2009
  38. 38. Adaptivity and agility Organization levels give means to express adaptive measures Level Changes Description Impact 1 Real-time adjustments • Elements change their interaction agreements to Low adapt to a certain situation. in the Interaction • Example: Two elements decide to use a different Model form of communication in response to new circumstances. 2 Real-time adjustments • A role is transferred from one element to another Medium element that is better qualified. in the Social Model. • Example: the ‘coordinator’ role is transferred from the actor in the control room to an actor in the field, because he is in a better position to coordinate other actors. 3 Real-time adjustments • The organization is redesigned to some degree. Severe This might involve added or deleting roles, changing in the Organizational objectives or behavior rules. Changes on this level Model might necessitate changes in the Social and Interaction Model too. • Example: Because several elements have stopped working, the objectives can no longer be reached. In response, new objectives are set with the remaining set of elements. 37 Teaming with Machines ISCRAM Summerschool 2009
  39. 39. Adaptivity and agility Approachs allows for gradual introduction of new elements For instance: introduce artificial actors at higher functional levels artificial actors at lower artificial actors at higher functional levels functional levels 38 Teaming with Machines ISCRAM Summerschool 2009
  40. 40. autonomy and task allocation choices between actors coordination and control methods information needs and accessibility 39 Teaming with Machines ISCRAM Summerschool 2009
  41. 41. FieldLab Indoor Safety and Security • Fieldlab Indoor Safety and Security • Components • Wireless positioning system • Network of smart cameras • Communication devices • Tracking and position prediction service • Information fusion services • Command center with common operational picture • Basic scenarios: intruder apprehension and incident management 40 Teaming with Machines ISCRAM Summerschool 2009
  42. 42. Fieldlab Indoor Safety and Security 41 Teaming with Machines ISCRAM Summerschool 2009
  43. 43. Experiments • Network built around a service oriented network (RESTlet) • Human contracts are still just ‘on paper’, but used strictly (before and during an experiment) • Some initial studies • transfer of the coordinator role from the central position to a mobile guard (role transfer among humans) • transfer intruder tracking role from the camera network to coordinator (task transfer from system to human) • transfer tracking from positioning system to coordinator (task transfer from system to human) • (Movie) 42 Teaming with Machines ISCRAM Summerschool 2009
  44. 44. Roles changes B 43 Teaming with Machines ISCRAM Summerschool 2009
  45. 45. Roles changes B 44 Teaming with Machines ISCRAM Summerschool 2009
  46. 46. Roles changes B 45 Teaming with Machines ISCRAM Summerschool 2009
  47. 47. Some observations • Observations • Using organizational models and contracts seems worthwhile to express adaptivity and interaction dynamics in man – machine organizations • Functional model helps to make basic allocation choices • it is easy to lose control over the situation after role change, especially for the coordinator role – even in the case of human – human role transfer. • Need for periodical synchronization of organization awareness and situation awareness is evident 46 Teaming with Machines ISCRAM Summerschool 2009
  48. 48. Concerns • Design concerns • Define who is responsible for role and task allocation • Set boundaries for dynamic allocation • Ensure observability of attributes and responsibilities • Make the type of adaptivity a design choice • Prevent issues caused by multi-level or multi-role allocation • Prevent communication and interaction issues after role change • Prevent loss of situation and system awareness among humans • Counter complacency and skill degredation • Prevent unneccessary increase of mental workload • Gradually build up user acceptance 47 Teaming with Machines ISCRAM Summerschool 2009
  49. 49. VIS Scenario 2009 B B B detectie • Incident observation and reconnaissance B SA • Incident assessment and plan Alarm creation Taak Alarm • Incident mitigation and DTA evacuation • Large set of virtual and actual B sensors command center • Players get adaptive B communication devices and new task coordination tools. B B B B 48 Teaming with Machines ISCRAM Summerschool 2009
  50. 50. Further developments Current developments: • Further formalize interaction contracts and contract management, especially between human and artificial actors • Explore dynamic task allocation schemes • Explore ways to balance self-organising capabilities and procedures • New series of experiments with additional technology (new services, new mobile devices, more sensors) and an extensive scenario (incident management and evacuation, larger set of human actors) Other applications under development: • Damage control teams aboard naval frigats • Various distributed sensor network applications • Training environments for civil firefighter teams 49 Teaming with Machines ISCRAM Summerschool 2009
  51. 51. Part III: Implications and Discussion Points to ponder Martijn Neef TNO Defence, Safety and Security
  52. 52. Implications • Machine teaming is not the stuff of science-fiction movies. It’s already here.. even though in simple forms.. • Technological advances will require us to rethink collaborative work. • We need to pay attention to autonomy, ethics and accountability. • Watch out for automation surprises and uncontrollable adaptivity. 51 Teaming with Machines ISCRAM Summerschool 2009
  53. 53. Discussion • Do you have any personal experiences (good or bad) with technology that resemble man – machine teaming? Or clearly show the need to rethink man – machine collaborations? • Can you imagine man – machine teaming scenarios for crisis response scenarios? • What would be the impact of such developments on crisis management organisations? Would the organisation actually change, or work differently? 52 Teaming with Machines ISCRAM Summerschool 2009
  54. 54. 53 Teaming with Machines ISCRAM Summerschool 2009
  55. 55. thank you for your attention! 54 Teaming with Machines ISCRAM Summerschool 2009
  56. 56. References (relevant own) • Neef, Martijn (2006), A Taxonomy of Human - Agent Team Collaborations. In Proceedings of the 18th BeNeLux Conference on Artificial Intelligence (BNAIC 2006), 5-6 October 2006, Namur, Belgium, pp. 245-250. • Neef, M., van Rijn, M., Keus, D., Marck, J-W. (2009), Organizing smart networks and humans into augmented teams. Proceedings of the 13th International Conference on Human-Computer Interaction, 19-24 July 2009, San Diego, CA, USA, Springer-Verlag: Lecture Notes on Computer Science, Berlin Heidelberg. • Neef, M., van der Vecht, B. (2009), Agility Through Adaptive Autonomy, Proceedings of the 14th International Command and Control Research and Technology Symposium (ICCRTS 2009), 15-17 June 2009, Washington D.C., USA. • Neef, M., Maanen, P.-P. van, Petiet, P., Spoelstra, M. (2009), Adaptive Work- Centered and Human-Aware Support Agents for Augmented Cognition in Tactical Environments. In: Proceedings of International Conference on Augmented Cognition, Jointly held with International Conference on Human-Computer Interaction, 2009 55 Teaming with Machines ISCRAM Summerschool 2009
  57. 57. References (others) • Salas, E., Dickinson, T. L., Converse, S. A., and Tannenbaum, S. I. (1992), Toward an understanding of team performance and training. In R. W. Swezey & E. Salas (Eds.), Teams: Their training and performance. Ablex, Norwood, USA, pp. 3-29. • Licklider, L.C.R. (1960), Man-Computer Symbiosis. IRE Transactions on Human Factors in Electronics, v.HFE-1, pp. 4-11. • Chalmers, B.A. (2001), Design frameworks for computer-based decision support. DREA Technical Memorandum, TM 2001-210, Defence Research Establishment Atlantic, Ottawa, Canada. • Fitts, P. M. (1951), Human Engineering for an Effective Air Navigation and Traffic Control System. National Research Council, Washington, D.C., USA. • Hoffman, R.R., Feltovich, P.J., Ford, K.M., Woods, D.D., Klein, G., Feltovich, A. (2002), A Rose by Any Other Name...Would Probably Be Given an Acronym. IEEE Intelligent Systems 17(4): 72-80 (2002) • Parasuraman, R., T. B. Sheridan, et al. (2000), A Model for Types and Levels of Human Interaction with Automation. IEEE Transactions on Systems, Man, and Cybernetics 30(3), pp. 286-297. 56 Teaming with Machines ISCRAM Summerschool 2009
  58. 58. References • Hollnagel, E. & Woods, D. D. (2005). Joint cognitive systems: Foundations of cognitive systems engineering. Boca Raton, FL: CRC Press / Taylor & Francis. • Klein, G., Woods, D.D., Bradshaw, J.M., Hoffman, R.R. and Feltovich, P.J. (2004), Ten Challenges for Making Automation a "Team Player" in Joint Human- Agent Activity. IEEE Intelligent Systems 19(6), pp. 91-95. • Bradshaw, J. M., Sierhuis, M., Acquisti, A., Feltovich, P., Hoffman, R., Jeffers, R., Prescott, D., Suri, N., Uszok, A., and Van Hoof, R. (2003), Adjustable autonomy and human - agent teamwork in practice: An interim report on space applications. In H. Hexmoor, R. Falcone, & C. Castelfranchi (eds.), Agent Autonomy, Dordrecht, The Netherlands: Kluwer, pp. 243-280. • Kester, L.J.H.M. (2008), Designing Networked Adaptive Interactive Hybrid Systems. Proceed-ings of the IEEE International Conference on Multisensor Fusion and Integration for Intelli-gent Systems 2008 (MFI2008), 20-22 August 2008, Seoul, Republic of Korea, pp. 516-521. • Dignum, V., Dignum, F., Meyer, J-J.Ch. (2004), An Agent-Mediated Approach to the Support of Knowledge Sharing in Organizations. Knowledge Engineering Review, Cambridge Uni-versity Press, 19(2), pp. 147-174. 57 Teaming with Machines ISCRAM Summerschool 2009

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