TANDEM: a trust-based agent framework for networked decision making

  • Sibel AdalıEmail author
  • Kevin Chan
  • Jin-Hee Cho


Team performance in networked decision making environments has been studied from many different perspectives. However, there are still many unanswered problems when it comes to understanding and quantifying the impact of individual differences of team players, their interpersonal relationships, team connectivity and complex interactions between these factors. In this paper, we present an agent framework that allows the manipulation of all these factors in a principled way. The agents in this framework can be connected through any network structure and can have different characteristics modeled in two dimensions of willingness and competence, which mirror beliefs for each other. Both nodes and links in the network can have differing capacity, modeled by agents’ ability to accomplish tasks and their trust for each other. The trust can change as a function of network activity, leading to dynamic scenarios. The framework is implemented as an open source simulation package and is fully extensible. With the help of an information sharing scenario, we conduct a sensitivity analysis and demonstrate the impact of all components of the framework on various network outcomes. In particular, we illustrate that the model provides the ability to study many different trade-offs in team performance and interaction between different parameters.


Agent based modeling Networks Decision making Trust 



Research was sponsored by the Army Research Laboratory and was accomplished under Cooperative Agreement Number W911NF-09-2-0053. The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the Army Research Laboratory or the U.S. Government. The U.S. Government is authorized to reproduce and distribute reprints for Government purposes notwithstanding any copyright notation here on. This research was also partially supported by the Department of Defense (DoD) through the office of the Assistant Secretary of Defense for Research and Engineering (ASD (R&E)). The views and opinions of the author(s) do not reflect those of the DoD nor ASD (R&E).

Supplementary material

10588_2015_9193_MOESM1_ESM.pdf (430 kb)
Supplementary material 1 (PDF 430 kb)


  1. Adalı S (2013) Modeling trust context in networks. Springer Briefs. Springer, New YorkCrossRefGoogle Scholar
  2. Alberts DS, Huber RK, Moffat J (2010) NATO NEC C2 maturity model. DoD command and control research programGoogle Scholar
  3. Bell S (2007) Deep-level composition variables as predictors of team performance: a meta-analysis. J Appl Psychol 92(3):595615CrossRefGoogle Scholar
  4. Bolstad CA, Endsley MR (2003) Tools for supporting team SA and collaboration in army operations. Collaborative technology alliances conferences: advanced decision archiecture conferenceGoogle Scholar
  5. Chan K, Adalı S (2012) An agent based model for trust and information sharing in networked systems. 2012 IEEE international multi-disciplinary conf on cognitive methods in situation awareness and decision supportGoogle Scholar
  6. Chan K, Ivanic N (2010) Connections between communications and social networks using ELICIT. In: Proceedings of 15th international command and control research and technology symposium, Santa Monica, CAGoogle Scholar
  7. Chan K, Cho JH, Adalı S (2013) A trust-based framework for information sharing behavior in command and control environments. 22nd conference on behavior representation in modeling and simulation (BRiMS)Google Scholar
  8. Cho J, Swami A, Chen IR (2011) A survey on trust management for mobile ad hoc networks. IEEE Commun Surveys and Tutor 13(4):562–583CrossRefGoogle Scholar
  9. Dekker T (2006) Centralization vs. self-synchronization: an agent-based investigation. In: Proceedings of 11th international command and control research and technology symposiumGoogle Scholar
  10. Edge AG, Remus W (1984) The impact of hierarchical and egalitarian organization structure on group decision making and attitudes. Dev Bus Simul Exp Learn 11:35–39Google Scholar
  11. Endsley MR (1995) Toward a theory of situation awareness in dynamic systems. Hum Factors 37(1):32–64CrossRefGoogle Scholar
  12. Fiske ST, Cuddy AJ, Glick P (2007) Universal dimensions of social cognition: warmth and competence. Trends Cogn Sci 11(2):77–83CrossRefPubMedGoogle Scholar
  13. Jacobides MG (2007) The inherent limits of organizational structure and the unfulfilled role of hierarchy: lessons from a near-war. Organ Sci 18(3):455–477CrossRefGoogle Scholar
  14. Katz N, Lazer D, Arrow H, Contractor N (2004) Network theory and small groups. Small Group Res 35:307–332CrossRefGoogle Scholar
  15. Levin DZ, Cross R (2002) The strength of weak ties you can trust: the mediating role of trust in effective knowledge transfer. Acad Manag J 50(11):1477–1490Google Scholar
  16. Leweling TA, Nissen ME (2007) Hypothesis testing of edge organizations: laboratory experimentation using the elicit multiplayer intelligence game. In: Proceedings of 12th international command and control research and technology symposiumGoogle Scholar
  17. Marksand MA, Mathieu JE, Zaccaro SJ (2001) A temporally based framework and taxonomy of team processes. Acad Manag Rev 26(3):356–376Google Scholar
  18. Mayer R, Davis J, Schoorman F (1995) An integrative model of organizational trust. Acad Manag Rev 20:709–734Google Scholar
  19. Mesmer-Magnus JR, DeChurch LA (2009) Information sharing and team performance: a meta-analysis. J Appl Psychol 94(2):535–546CrossRefPubMedGoogle Scholar
  20. Morgan R (2008) Company intelligence support teams. Armor MagGoogle Scholar
  21. United States Office of the Director of National Intelligence (2008) United States Intelligence Community Information Sharing Strategy Online:
  22. Stevens M, Campion M (1994) The knowledge, skill, and ability requirements for teamwork: Implications for human resource management. J Manag 20:503–530Google Scholar
  23. Stinchcombe A (1965) Social structure and environment. In: March JG (ed) The handbook of organizations. University of California Press, Berkeley, pp 142–193Google Scholar
  24. Suri S, Watts DJ (2011) Cooperation and contagion in web-based, networked public goods experiments. PLoS ONE 6(3). doi: 10.1371/journal.pone.0016836
  25. Thunholm P, Chong NE, Cheah M, Tan K, Chua N, Chua CL (2009) Exploring alternative edge versus hierarchy C2 organizations using the elicit platform with configurable chat system. Int Command Control (C2) J 3(2)Google Scholar
  26. Uzzi B (1996) The sources and consequences of embeddedness for the economic performance of organizations: the network effect. Am Sociol Rev 61:674–698CrossRefGoogle Scholar
  27. Uzzi B (2008) A social network’s changing statistical properties and the quality of human innovation. J Phys A 41:224023MathSciNetCrossRefADSGoogle Scholar
  28. Wout V, Sanfey A (2008) Friend or foe: the effect of implicit trustworthiness judgments in social decision-making. Cognition 108(3):796–803CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  1. 1.Department of Computer ScienceRensselaer Polytechnic InstituteTroyUSA
  2. 2.Computational & Information Sciences Directorate (CISD)U.S. Army Research Laboratory (USARL)AdelphiUSA

Personalised recommendations