Demonstrative experiments with RBot and MRS--论文代写范文精选

如果数据转换准确，这适用于开发过程中的阶段,由于数据是必需的。问题的准确性是将问题公式化，作为一个可执行的计算机程序。如正确初始化模型和创建一个模型,该模型符合实际问题。下面的论文代写范文进行论述。

Introduction
  In this chapter, we verify and validate the working of the toolkit with help of demonstrative experiments, i.e. the experiments will demonstrate that RBot and MRS are capable of modelling social situations with the help of cognitive plausible actors. In chapter 1, we introduced the design-based approach and simulation as methodology. We explained the life cycle of a simulation study that contains a conceptual model of the real world, the computer model and the experimental model that results in solutions and understanding of the real world situation. 

  In this chapter, we continue the discussion with regards to the verication and validation of our computer model and our demonstrative experiments, i.e. the chapter discusses how the combination of RBot and MRSa combined tool for creating simulationsis veried and validated. This will be demonstrated with the help of (1) an experiment that compares the inner working of RBot with that of ACT-R, and (2) two experiments of which one will demonstrate the working of RBot actors in a multi-actor environment (MRS), and the other the working of the social construct as a coordination mechanism for RBot actors that enables them to be socially situated. 6.

  Verication, Validation and Testing Probably the most important step in developing a model is the stage of veri- cation and validation. Users and developers that use information derived from the results of the model should be concerned with whether the results of such a model reect the real problem they are trying to research. The concern of getting a successful model is addressed with the help of verication and validation (Moss, Edmonds, & Wallis, 1997, pp. 23).

  Data Verication: determining that the contextual data, the data required for model realization and verication, and if any data transformations are suf- ciently accurate. This applies to all stages in the development process, since data is required at every point. 
Program Validation: concerns the accuracy of transforming a problem formulation/converting a model representation into an executable computer program. 
  Experiment Validation: concerns the accuracy of implementing a specic problem into an experiment model, e.g. initializing the model correctly and creating a model that conforms to a real problem or a predened articial world. 
  Experimentation Validation: determining that the experimental procedures adopted are providing results that are sufciently accurate for the purpose at hand. Key issues are the requirements for removing initialization bias, run-length, replications and sensitivity analysis to assure the accuracy of the results. 
  Solution Verication: determining that the results obtained from the model of the proposed solution are sufciently accurate for the purpose at hand. This is similar to black-box3 validation (or better verication) in that it entails comparison with the real world. 

  The most common felt problem with verication and validation is that even when a thoroughly verication and validation process has been undertaken, there are still some difculties to be recognized (Robinson, 2004, p. 213). Some difculties can arise such as (1) there is no real world to compare against (e.g. our articial society), (2) people have different interpretations of the real world (the perceived world), i.e. if one person claims a model to be veried and validated, someone else claims it is not, (3) the real data collected might be inaccurate due to incorrect collection of data, or a too short time period of collection causing the model to be valid only for that specic period and not for other periods, (4) the cost and amount of time needed for validation and verication is often too high to create a sufcient and complete verication and validation process. 

 Validation methods and techniques 
  Probably the most important part of research and of creating simulation models is determining the appropriate validation methods and techniques. For a thoroughly validation and verication of simulation models, there exist many techniques to choose from (Whitner & Balci, 1989; Balci, 1998). In this dissertation, we want to provide a collection of techniques stated by Sargent (2000, pp. 5253)4 .The verication and validation techniques discussed here are applicable to operational validity. Operational validity is concerned with determining that the model's output behavior has the accuracy required for the model's intended purpose over the domain of its intended applicability (Sargent, 2000, p. 54). The validation techniques can be applied either subjectivelye.g. looking at the models behaviour, or objectivelyusing statistics to get an (more) independent judgement of the model. The other attribute is whether the system is observable, i.e. is it possible to collect data about the operational behaviour of the real world problem (system). 

 Demonstrative experiments 
  The rst demonstrative experiment, as explained before, consists of a single actor experiment. The purpose of the experiment is to compare the behaviour of the RBot model with that of the ACT-R architecture. The experiment is concerned with the validity of RBot and aims at nding out whether the behaviour of RBot matches the behaviour of ACT-R as a cognitive architecture. The other two experiments describe an interaction between two actors and are concerned with the construction of an `articial society'. The implementation of such a society with help of RBot and MRS allows us to test and demonstrate whether certain assumptions about behaviour, e.g. the inuence and change of social constructs, can be made explicit with help of a simulation model. Hence, it allows us to (1) demonstrate that something is possible and (2) suggest ideas (Holland, 1998). We will rst discuss the single actor experiment.

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