A domain specific language for complex dynamic decision making

Effective decision making of organisation requires deep understanding of various organisational aspects such as its goals, structure, business-as-usual operational processes in the context of dynamic, socio-technical and uncertain business envi-ronment. Decision making approaches adopt a range of modelling and analysis techniques for effective decision making. The current state-of-practice of deci-sion-making typically relies heavily on human experts using intuition aided by ad-hoc representation of an organisation. Existing technologies for decision mak-ing are not able to represent all constructs that are needed for effective decision making nor do they comprehensively address the analysis needs. This paper pro-poses a meta-model to represent organisation and decision artifacts in a compre-hensive, relatable and analysable form that serves as a basis for a domain specific language (DSL) for complex dynamic decision making. The efficacy of the pro-posed meta-model as regards specification and analysis is evaluated using a real-life scenario.

[1]  H. Simon,et al.  A Behavioral Model of Rational Choice , 1955 .

[2]  Michael X Cohen,et al.  A Garbage Can Model of Organizational Choice. , 1972 .

[3]  Henry Mintzberg,et al.  The Structure of "Unstructured" Decision Processes , 1976 .

[4]  John A. Zachman,et al.  A Framework for Information Systems Architecture , 1987, IBM Syst. J..

[5]  Jack P. C. Kleijnen,et al.  Verification and validation of simulation models , 1995 .

[6]  Jaegwon Kim,et al.  Emergence or Reduction?: Essays on the Prospects of Nonreductive Physicalism , 1992 .

[7]  Ulrich Frank,et al.  Multi-perspective enterprise modeling (MEMO) conceptual framework and modeling languages , 2002, Proceedings of the 35th Annual Hawaii International Conference on System Sciences.

[8]  Eric Bonabeau,et al.  Agent-based modeling: Methods and techniques for simulating human systems , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[9]  Michael J. North,et al.  Tutorial on agent-based modelling and simulation , 2005, Proceedings of the Winter Simulation Conference, 2005..

[10]  K. McLeroy Thinking of Systems , 2006 .

[11]  Markus Strohmaier,et al.  Exploring Intentional Modeling and Analysis for Enterprise Architecture , 2006, 2006 10th IEEE International Enterprise Distributed Object Computing Conference Workshops (EDOCW'06).

[12]  Martin Odersky,et al.  Scala Actors: Unifying thread-based and event-based programming , 2009, Theor. Comput. Sci..

[13]  Carl Hewitt,et al.  Actor Model of Computation: Scalable Robust Information Systems , 2010, 1008.1459.

[14]  Laurent Ciarletta,et al.  Agents and artefacts for multiple models co-evolution: building complex system simulation as a set of interacting models , 2010, AAMAS.

[15]  Petra Wächter Thinking in systems – a primer , 2011 .

[16]  Remco M. Dijkman,et al.  Business Process Model and Notation - Third International Workshop, BPMN 2011, Lucerne, Switzerland, November 21-22, 2011. Proceedings , 2011, Business Process Modeling Notation.

[17]  Donald H. Rumsfeld Known and Unknown: A Memoir , 2011 .

[18]  P. Yu Multiple-Criteria Decision Making: "Concepts, Techniques, And Extensions" , 2012 .

[19]  Jan Mendling,et al.  Business Process Model and Notation , 2012, Lecture Notes in Business Information Processing.

[20]  Vinay Kulkarni,et al.  Towards business application product lines , 2012, MODELS'12.

[21]  Roel Wieringa,et al.  Technical Action Research as a Validation Method in Information Systems Design Science , 2012, DESRIST.

[22]  Tom McDermott,et al.  Multi-level Modeling of Complex Socio-Technical Systems , 2013, CSER.

[23]  Jamie Allen Effective Akka , 2013 .

[24]  Emilio Insfran,et al.  Model-Driven Engineering Languages and Systems , 2014, Lecture Notes in Computer Science.

[25]  Vinay Kulkarni,et al.  Using simulation to address intrinsic complexity in multi-modelling of enterprises for decision making , 2015, SummerSim.

[26]  Vinay Kulkarni,et al.  Toward overcoming accidental complexity in organisational decision-making , 2015, 2015 ACM/IEEE 18th International Conference on Model Driven Engineering Languages and Systems (MODELS).

[27]  Vincent Chevrier,et al.  Combining DEVS with multi-agent concepts to design and simulate multi-models of complex systems (WIP) , 2015, SpringSim.

[28]  Robert Winter,et al.  Enterprise Modelling for the Masses - From Elitist Discipline to Common Practice , 2016, PoEM.

[29]  Vinay Kulkarni,et al.  Enterprise Modeling as a Decision Making Aid: A Systematic Mapping Study , 2016, PoEM.

[30]  Vinay Kulkarni,et al.  ESL: An Actor-Based Platform for Developing Emergent Behaviour Organisation Simulations , 2017, PAAMS.

[31]  J. March,et al.  Organisational decision-making , 2019, Delivering Better Policies Through Behavioural Insights.

[32]  Timothy O’Connor,et al.  EMERGENT PROPERTIES , 2021 .

[33]  M. Iacob,et al.  State of the Art in Architecture Support , 2022 .