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A Software Interface
Between System
Dynamics and Agent-
Based Simulations
A study by
Andreas Gr旦ler,
Myrjam Stotz,
and
Nadine Schieritz
Mannheim University,
Germany
Agent-Based Simulation
Whereas in system dynamics the internal structure of a
system determines its dynamic tendencies, in the agent-
based simulation the dynamic behavior of a system arises
from the behavior of its elements, the agents, and the
interactions between them:

System Dynamics Agent-Based
Simulation
Basic building
block
Feedback loop Agent
Unit of analysis Structure Agents' rules
Level of modeling Macro Micro
Perspective Top-down Bottom-up
Scientific Problem
Agent-based simulation and system
dynamics use computer simulation to
investigate social and economic systems
characterized by non-linearity, delays and
feedback processes.
Both concentrate on understanding and
qualitative prediction of systems behavior.
 An integration of both approaches
might be fruitful.
The Software Used
A software
framework for
creating agent
based simulations
using the Java
language
A visual modeling
tool for system
dynamic models
The Vensim DLL
allows you to call
Vensim functions
from other
applications
The Technical Integration
At least two Java classes have to be programmed:
the simulation environment and the agents class
Java class of the
simulation
environment
 Based on a class
given by RePast
 Builds and
manages the agents
 Manages the
simulation
 Provides a
graphical user
interface
Java class of
the agents
 Represents the
mental model of
the agents
 Builds a Vensim
object to
communicate with
Vensim via the
Vensim DLL
Vensim object
(provided by
Vensim)
 Calls the Vensim
DLL
 Manages the
transfer of data and
commands
between the agent-
class and Vensim
provides creates creates calls
An example from Supply Chain
Management
Supplier
Agent
Manufacturer
Agent1
Manufacturer
Agent2
Manufacturer
Agent3
Behavior of the
manufacturer
RePast VensimDLL
Agent-based simulation System Dynamics
Behavior of the
manufacturer
Behavior of the
manufacturer
The Agents Behavior
Inventory
Acquisition Rate Shipment
Rate
Desired
Acquisition Rate
Acquisition
Adjustment from
Inventory
Desired
Inventory
Expected
Order Rate Change in
Exp Orders
Inventory
Adjustment
Time
Desired
Inventory
Coverage
Time to Average
Order Rate
Order
Fulfillment
Ratio
Table for Order
Fulfillment
Supply LineOrders Placed
Rate
Acquisition Lag
Adjustment for
Supply Line
Desired
Supply Line
Orders Placed
Supply Line
Adjustment Time
Customer
Order Rate
B
Order
Fulfillment
B Inventory Control
B
Supply Line
Control -
-
+
+
+
+
+
- -
+
+
-
+
+
+
-
Desired
Shipment
Rate
+
Maximum
Shipment
Rate
Minimum
Order
Processing
Time
+
+
-
-
+
Inventory
Coverage
+ -
Safety
Stock
Coverage
+
+
+
Customer
Orders
Backlog Backlog
Change Rate
+ -
+
Supplies
Received
Init Supply Line Init Inventory
Init Expected
Order Rate Init Customer
Orders Backlog
+
+
In each step of a simulation the agent-based modeled manufacturers
call this System Dynamics model (modified after Sterman 2000)...
The Simulation in RePast Start and stop
a simulation
Graphs represent
the results of
simulations
In a probe map
parameters of the
simulation can be set
Conclusions
 The presented software solution provides a
prototypical common technical platform to
examine problems that suggest the
integration of the two simulation concepts
 More flexibility is provided in modeling and
simulating dynamic systems (using in each
part of the model the method fitting best)
 The advantages of both methods can be used,
their disadvantages can be reduced
 Skills in Java are necessary
Further Research
 Extend and improve the model technically,
e.g. make simulations more user-friendly
 Use this platform to model other problems
that suggest the integration of the two
simulation concepts
 Use this software interface as a basis to model
an integration with System Dynamics on
macro-level and agent-based simulations on
micro-level
 Investigate effects of combined methods on
validity of models
References
 RePast: http://repast.sourceforge.net
 Venism: http://www.vensim.com
 Phelan, SE. 1999. A Note on the Correspondence between
Complexity and Systems Theory. Systemic Practice and
Action Research 12(3): 237246.
 Schieritz, N, Gr旦ler, A. 2003. Emergent Structures in Supply
Chains: A Study Integrating Agent-Based and System
Dynamics Modeling. Proceedings of the 36th Hawaiian
International Conference on Systems Science, Wailea.
 Scholl, HJ. 2001a. Agent-based and System Dynamics
Modeling: A Call for Cross Study and Joint Research.
Proceedings of the 34th Hawaiian International Conference
on Systems Science, Wailea.
 Sterman, JD. 2000. Business Dynamics  Systems Thinking
and Modeling for a Complex World, Boston.

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Poster Vensim Repast

  • 1. A Software Interface Between System Dynamics and Agent- Based Simulations
  • 2. A study by Andreas Gr旦ler, Myrjam Stotz, and Nadine Schieritz Mannheim University, Germany
  • 3. Agent-Based Simulation Whereas in system dynamics the internal structure of a system determines its dynamic tendencies, in the agent- based simulation the dynamic behavior of a system arises from the behavior of its elements, the agents, and the interactions between them: System Dynamics Agent-Based Simulation Basic building block Feedback loop Agent Unit of analysis Structure Agents' rules Level of modeling Macro Micro Perspective Top-down Bottom-up
  • 4. Scientific Problem Agent-based simulation and system dynamics use computer simulation to investigate social and economic systems characterized by non-linearity, delays and feedback processes. Both concentrate on understanding and qualitative prediction of systems behavior. An integration of both approaches might be fruitful.
  • 5. The Software Used A software framework for creating agent based simulations using the Java language A visual modeling tool for system dynamic models The Vensim DLL allows you to call Vensim functions from other applications
  • 6. The Technical Integration At least two Java classes have to be programmed: the simulation environment and the agents class Java class of the simulation environment Based on a class given by RePast Builds and manages the agents Manages the simulation Provides a graphical user interface Java class of the agents Represents the mental model of the agents Builds a Vensim object to communicate with Vensim via the Vensim DLL Vensim object (provided by Vensim) Calls the Vensim DLL Manages the transfer of data and commands between the agent- class and Vensim provides creates creates calls
  • 7. An example from Supply Chain Management Supplier Agent Manufacturer Agent1 Manufacturer Agent2 Manufacturer Agent3 Behavior of the manufacturer RePast VensimDLL Agent-based simulation System Dynamics Behavior of the manufacturer Behavior of the manufacturer
  • 8. The Agents Behavior Inventory Acquisition Rate Shipment Rate Desired Acquisition Rate Acquisition Adjustment from Inventory Desired Inventory Expected Order Rate Change in Exp Orders Inventory Adjustment Time Desired Inventory Coverage Time to Average Order Rate Order Fulfillment Ratio Table for Order Fulfillment Supply LineOrders Placed Rate Acquisition Lag Adjustment for Supply Line Desired Supply Line Orders Placed Supply Line Adjustment Time Customer Order Rate B Order Fulfillment B Inventory Control B Supply Line Control - - + + + + + - - + + - + + + - Desired Shipment Rate + Maximum Shipment Rate Minimum Order Processing Time + + - - + Inventory Coverage + - Safety Stock Coverage + + + Customer Orders Backlog Backlog Change Rate + - + Supplies Received Init Supply Line Init Inventory Init Expected Order Rate Init Customer Orders Backlog + + In each step of a simulation the agent-based modeled manufacturers call this System Dynamics model (modified after Sterman 2000)...
  • 9. The Simulation in RePast Start and stop a simulation Graphs represent the results of simulations In a probe map parameters of the simulation can be set
  • 10. Conclusions The presented software solution provides a prototypical common technical platform to examine problems that suggest the integration of the two simulation concepts More flexibility is provided in modeling and simulating dynamic systems (using in each part of the model the method fitting best) The advantages of both methods can be used, their disadvantages can be reduced Skills in Java are necessary
  • 11. Further Research Extend and improve the model technically, e.g. make simulations more user-friendly Use this platform to model other problems that suggest the integration of the two simulation concepts Use this software interface as a basis to model an integration with System Dynamics on macro-level and agent-based simulations on micro-level Investigate effects of combined methods on validity of models
  • 12. References RePast: http://repast.sourceforge.net Venism: http://www.vensim.com Phelan, SE. 1999. A Note on the Correspondence between Complexity and Systems Theory. Systemic Practice and Action Research 12(3): 237246. Schieritz, N, Gr旦ler, A. 2003. Emergent Structures in Supply Chains: A Study Integrating Agent-Based and System Dynamics Modeling. Proceedings of the 36th Hawaiian International Conference on Systems Science, Wailea. Scholl, HJ. 2001a. Agent-based and System Dynamics Modeling: A Call for Cross Study and Joint Research. Proceedings of the 34th Hawaiian International Conference on Systems Science, Wailea. Sterman, JD. 2000. Business Dynamics Systems Thinking and Modeling for a Complex World, Boston.