Querying histories of organisation simulations

Industrial Dynamics involves system modelling, simulation and evaluation leading to policy making. Traditional approaches to industrial dynamics use expert knowledge to build top-down models that have been criticised as not taking into account the adaptability and sociotechnical features of modern organisations. Furthermore, such models require a-priori knowledge of policy-making theorems. This paper advances recent research on bottom-up agent-based organisational modelling for Industrial Dynamics by presenting a framework where simulations produce histories that can be used to establish a range of policy-based theorems. The framework is presented and evaluated using a case study that has been implemented using a toolset called ES

Querying histories of organisation simulations

Industrial Dynamics involves system modelling, simulation and evaluation leading to policy making. Traditional approaches to industrial dynamics use expert knowledge to build top-down models that have been criticised as not taking into account the adaptability and sociotechnical features of modern organisations. Furthermore, such models require a-priori knowledge of policy-making theorems. This paper advances recent research on bottom-up agent-based organisational modelling for Industrial Dynamics by presenting a framework where simulations produce histories that can be used to establish a range of policy-based theorems. The framework is presented and evaluated using a case study that has been implemented using a toolset called ES

The construction and interrogation of actor based simulation histories

Large socio-technical systems are complex to comprehend in their entirety because information exchanges between system compo- nents lend an emergent nature to the overall system behaviour. Although Individual system component behaviour may be known at the outset, such components may exhibit uncertainty and further exacerbate issues of a priori prediction of the overall system behaviour. Multi-agent sys- tems and the use of simulation is a possible recourse in such situations however, simulation results need to be correctly interpreted so as to nudge the overall system behaviour towards a desired objective. We pro- pose a solution wherein the system is modelled as a set of actors ex- changing messages, a simulation engine producing execution trace for an actor as its history, and a querying mechanism to identify patterns that may span across individual actor histories to ascertain property of the overall system. The proposed solution is evaluated using a representative sample from real life

Principles and Concepts of Agent-Based Modelling for Developing Geospatial Simulations

The aim of this paper is to outline fundamental concepts and principles of the Agent-Based Modelling (ABM) paradigm, with particular reference to the development of geospatial simulations. The paper begins with a brief definition of modelling, followed by a classification of model types, and a comment regarding a shift (in certain circumstances) towards modelling systems at the individual-level. In particular, automata approaches (e.g. Cellular Automata, CA, and ABM) have been particularly popular, with ABM moving to the fore. A definition of agents and agent-based models is given; identifying their advantages and disadvantages, especially in relation to geospatial modelling. The potential use of agent-based models is discussed, and how-to instructions for developing an agent-based model are provided. Types of simulation / modelling systems available for ABM are defined, supplemented with criteria to consider before choosing a particular system for a modelling endeavour. Information pertaining to a selection of simulation / modelling systems (Swarm, MASON, Repast, StarLogo, NetLogo, OBEUS, AgentSheets and AnyLogic) is provided, categorised by their licensing policy (open source, shareware / freeware and proprietary systems). The evaluation (i.e. verification, calibration, validation and analysis) of agent-based models and their output is examined, and noteworthy applications are discussed.Geographical Information Systems (GIS) are a particularly useful medium for representing model input and output of a geospatial nature. However, GIS are not well suited to dynamic modelling (e.g. ABM). In particular, problems of representing time and change within GIS are highlighted. Consequently, this paper explores the opportunity of linking (through coupling or integration / embedding) a GIS with a simulation / modelling system purposely built, and therefore better suited to supporting the requirements of ABM. This paper concludes with a synthesis of the discussion that has proceeded. The aim of this paper is to outline fundamental concepts and principles of the Agent-Based Modelling (ABM) paradigm, with particular reference to the development of geospatial simulations. The paper begins with a brief definition of modelling, followed by a classification of model types, and a comment regarding a shift (in certain circumstances) towards modelling systems at the individual-level. In particular, automata approaches (e.g. Cellular Automata, CA, and ABM) have been particularly popular, with ABM moving to the fore. A definition of agents and agent-based models is given; identifying their advantages and disadvantages, especially in relation to geospatial modelling. The potential use of agent-based models is discussed, and how-to instructions for developing an agent-based model are provided. Types of simulation / modelling systems available for ABM are defined, supplemented with criteria to consider before choosing a particular system for a modelling endeavour. Information pertaining to a selection of simulation / modelling systems (Swarm, MASON, Repast, StarLogo, NetLogo, OBEUS, AgentSheets and AnyLogic) is provided, categorised by their licensing policy (open source, shareware / freeware and proprietary systems). The evaluation (i.e. verification, calibration, validation and analysis) of agent-based models and their output is examined, and noteworthy applications are discussed.Geographical Information Systems (GIS) are a particularly useful medium for representing model input and output of a geospatial nature. However, GIS are not well suited to dynamic modelling (e.g. ABM). In particular, problems of representing time and change within GIS are highlighted. Consequently, this paper explores the opportunity of linking (through coupling or integration / embedding) a GIS with a simulation / modelling system purposely built, and therefore better suited to supporting the requirements of ABM. This paper concludes with a synthesis of the discussion that has proceeded

Constructing and interrogating actor histories

Complex systems, such as organizations, can be represented as executable simulation models using actor-based languages. Decision-making can be supported by system simulation so that different configurations provide a basis for what-if analysis. Actor-based models are expressed in terms of large numbers of concurrent actors that communicate using asynchronous messages leading to complex non-deterministic behaviour. This chapter addresses the problem of analyzing the results of model executions and proposes a general approach that can be added to any actor-based system. The approach uses a logic programming language with temporal extensions to query execution traces. The approach has been implemented and is shown to support a representative system model

Constructing and interrogating actor histories

Complex systems, such as organizations, can be represented as executable simulation models using actor-based languages. Decision-making can be supported by system simulation so that different configurations provide a basis for what-if analysis. Actor-based models are expressed in terms of large numbers of concurrent actors that communicate using asynchronous messages leading to complex non-deterministic behaviour. This chapter addresses the problem of analyzing the results of model executions and proposes a general approach that can be added to any actor-based system. The approach uses a logic programming language with temporal extensions to query execution traces. The approach has been implemented and is shown to support a representative system model

Intelligent Data Storage and Retrieval for Design Optimisation – an Overview

This paper documents the findings of a literature review conducted by the Sir Lawrence Wackett Centre for Aerospace Design Technology at RMIT University. The review investigates aspects of a proposed system for intelligent design optimisation. Such a system would be capable of efficiently storing (and compressing if required) a range of types of design data into an intelligent database. This database would be accessed by the system during subsequent design processes, allowing for search of relevant design data for re-use in later designs, allowing it to become very efficient in reducing the time for later designs as the database grows in size. Extensive research has been performed, in both theoretical aspects of the project, and practical examples of current similar systems. This research covers the areas of database systems, database queries, representation and compression of design data, geometric representation and heuristic methods for design applications.

CHORUS Deliverable 2.1: State of the Art on Multimedia Search Engines

Based on the information provided by European projects and national initiatives related to multimedia search as well as domains experts that participated in the CHORUS Think-thanks and workshops, this document reports on the state of the art related to multimedia content search from, a technical, and socio-economic perspective. The technical perspective includes an up to date view on content based indexing and retrieval technologies, multimedia search in the context of mobile devices and peer-to-peer networks, and an overview of current evaluation and benchmark inititiatives to measure the performance of multimedia search engines. From a socio-economic perspective we inventorize the impact and legal consequences of these technical advances and point out future directions of research

The representation and management of evolving features in geospatial databases

Geographic features change over time, this change being the result of some kind of event or occurrence. It has been a research challenge to represent this data in a manner that reflects human perception. Most database systems used in geographic information systems (GIS) are relational, and change is either captured by exhaustively storing all versions of data, or updates replace previous versions. This stems from the inherent diffculty of modelling geographic objects in relational tables. This diffculty is compounded when the necessary time dimension is introduced to model how those objects evolve. There is little doubt that the object-oriented (OO) paradigm holds signi cant advantages over the relational model when it comes to modelling real-world entities and spatial data, and it is argued that this contention is particularly true when it comes to spatio-temporal data. This thesis describes an object-oriented approach to the design of a conceptual model for representing spatio-temporal geographic data, called the Feature Evolution Model (FEM), based on states and events. The model was used to implement a spatio-temporal database management system in Oracle Spatial, and an interface prototype is described that was used to evaluate the system by enabling querying and visualisation

TOWARDS ADAPTIVE ENTERPRISES USING DIGITAL TWINS

Modern enterprises are large complex systems operating in highly dynamic environments thus requiring quick response to a variety of change drivers. Moreover, they are systems of systems wherein understanding is available in localized contexts only and that too is typically partial and uncertain. With the overall system behaviour hard to know a-priori and conventional techniques for system-wide analysis either lacking in rigour or defeated by the scale of the problem, the current practice often exclusively relies on human expertise for monitoring and adaptation. We present an approach that combines ideas from modeling & simulation, reinforcement learning and control theory to make enterprises adaptive. The approach hinges on the concept of Digital Twin - a set of relevant models that are amenable to analysis and simulation. The paper describes illustration of approach in two real world use cases