Modelling and analysing human behaviour in a department store using discrete event and agent based simulation

Discrete Event Simulation (DES) is a very popular simulation technique in Operational Research. Recently, there has been the emergence of another technique, namely Agent Based Simulation (ABS). Although there is a lot of literature relating to DES and ABS, we have found less that focuses on exploring the capabilities of both in tackling human behaviour issues. In order to understand the gap between these two simulation techniques, therefore, our aim is to understand the distinctions between DES and ABS models with the real world phenomenon in modelling and simulating human behaviour. In achieving the aim, we have carried out a case study at a department store. Both DES and ABS models will be compared using the same problem domain which is concerning on management policy in a fitting room. The behaviour of staffs while working and customers’ satisfaction will be modelled for both models behaviour understanding.

Exploring Change in Neanderthal Behavioural Complexity: An Innovative Approach to the Study of Neanderthal Behaviour

Diachronic approaches provide potential for a more sophisticated framework within which to examine change in Neanderthal behavioural complexity using archaeological proxies such as symbolic artefacts, faunal assemblages and technology. Analysis of the temporal appearance and distribution of such artefacts and assemblages provide the basis for identifying changes in Neanderthal behavioural complexity in terms of symbolism, faunal extraction and technology respectively. Although changes in technology and faunal extraction were examined in the wider study, only the results of the symbolic study are presented below to illustrate the potential of the approach.

A framework to understand human action

This paper consists in an analysis of two explanatory models of human behaviour which play a prominent role in the contemporary literature on human action. The first model - the causalist - aims at explaining action in terms of causes and general laws. The second model - the intentionalist - explains human action in terms of intentions and practical syllogism. The difficulties of both models are presented and in the last part of the essay we propose one alternative model, based on the notion of retroduction.

A review of palaeoclimates and palaeoenvironments in the Levant and Eastern Mediterranean from 25,000 to 5000 years BP: setting the environmental background for the evolution of human civilisation

The southern Levant has a long history of human habitation and it has been previously suggested that climatic changes during the Late Pleistocene-Holocene stimulated changes in human behaviour and society. In order to evaluate such linkages, it is necessary to have a detailed understanding of the climate record. We have conducted an extensive and up-to-date review of terrestrial and marine climatic conditions in the Levant and Eastern Mediterranean during the last 25,000 years. We firstly present data from general circulation models (GCMs) simulating the climate for the last glacial maximum (LGM), and evaluate the output of the model by reference to geological climate proxy data. We consider the types of climate data available from different environments and proxies and then present the spatial climatic "picture" for key climatic events. This exercise suggests that the major Northern Hemisphere climatic fluctuations of the last 25,000 years are recorded in the Eastern Mediterranean and Levantine region. However, this review also highlights problems and inadequacies with the existing data. (c) 2006 Elsevier Ltd. All rights reserved.

A survey of human motion analysis using depth imagery

Analysis of human behaviour through visual information has been a highly active research topic in the computer vision community. This was previously achieved via images from a conventional camera, but recently depth sensors have made a new type of data available. This survey starts by explaining the advantages of depth imagery, then describes the new sensors that are available to obtain it. In particular, the Microsoft Kinect has made high-resolution real-time depth cheaply available. The main published research on the use of depth imagery for analysing human activity is reviewed. Much of the existing work focuses on body part detection and pose estimation. A growing research area addresses the recognition of human actions. The publicly available datasets that include depth imagery are listed, as are the software libraries that can acquire it from a sensor. This survey concludes by summarising the current state of work on this topic, and pointing out promising future research directions.

A framework to understand human action

O trabalho consiste numa análise de dois modelos explicativos do comportamento humano considerados fundamentais na literatura contemporânea sobre teoria da ação. O primeiro modelo, o causalista, tenta explicar as ações em termos de causas e leis gerais. O segundo explica a ação em termos de intenções e silogismos práticos. As dificuldades e problemas de ambos modelos são apresentadas e na última parte do ensaio propomos um modelo alternativo baseado na noção de retrodução.

Car Design and Road Crossing Behaviour

Humans possess a highly developed sensitivity for facial features. This sensitivity is also deployed to non-human beings and inanimate objects such as cars. In the present study we aimed to investigate whether car design has a bearing on the behaviour of pedestrians. Methods: An immersive virtual reality environment with a zebra crossing was used to determine a) whether the minimum accepted distance for crossing the street is bigger for cars with dominant appearance than for cars with friendly appearance (Block 1) and b) whether the speed of dominant cars are overestimated compared to friendly cars (Block 2). In Block 1, the participant's task was to cross the road in front of an approaching car at the latest moment. The point of time when entering and leaving the street was measured. In Block 2 they were asked to estimate the speed of each passing car. An independent sample rated dominant cars as being more dominant, angry and hostile than friendly cars. Results: None of the predictions regarding the car design was confirmed. Instead, there was an effect of starting position: From the centre island, participants entered the road significantly later (smaller accepted distance) and left the road later than when starting from the pavement. Consistently, the speed of the cars was estimated significantly lower when standing on the centre island compared to the pavement. When entering the visual size of the cars as factor (instead of dominance), we found that participants started to cross the road significantly later in front of small cars compared to big cars and that the speed of smaller cars was overestimated compared to big cars (size-speed bias). Conclusions: Car size and starting position, not car design seem to have an influence on road crossing behaviour.

Decomposition of human behavior using model of competencies: application to robotic control system

For many years, humans and machines have shared the same physical space. To facilitate their interaction with humans, their social integration and for more rational behavior has been sought that the robots demonstrate human-like behavior. For this it is necessary to understand how human behavior is generated, discuss what tasks are performed and how relate to themselves, for subsequent implementation in robots. In this paper, we propose a model of competencies based on human neuroregulator system for analysis and decomposition of behavior into functional modules. Using this model allow separate and locate the tasks to be implemented in a robot that displays human-like behavior. As an example, we show the application of model to the autonomous movement behavior on unfamiliar environments and its implementation in various simulated and real robots with different physical configurations and physical devices of different nature. The main result of this work has been to build a model of competencies that is being used to build robotic systems capable of displaying behaviors similar to humans and consider the specific characteristics of robots.

Approach to challenging behaviour: a family affair

Over the past 30 years, research in the area of applied behaviour. analysis has led to a rich knowledge and understanding of the variables that influence human behaviour. This understanding and knowledge has given rise to a range of assessment and intervention techniques that have been applied to individuals with challenging behaviour. Interventions have produced changes in the severity and frequency of behaviours such as self-injury, aggression, and property destruction, card have also led to the acquisition of desired behaviours. While behaviour change has been achieved, families have expressed a desire for positive behaviour support approaches that adopt a family,focus. Research and development of support frameworks that emphasise the interrelatedness of family members, and the child with a disability as part of his or her family, have gained prominence in the family systems literature. The present paper reviews some of the behaviourally based research in this area. Through the use of a case illustration, the authors discuss the links between behavioural support and family-centred support systems for children with developmental disabilities. Theoretical and practical implications are considered and areas for future research are highlighted.

Hierarchical Task Network Planning with Common-Sense Reasoning for Multiple-People Behaviour Analysis

Safety on public transport is a major concern for the relevant authorities. We
address this issue by proposing an automated surveillance platform which combines data from video, infrared and pressure sensors. Data homogenisation and integration is achieved by a distributed architecture based on communication middleware that resolves interconnection issues, thereby enabling data modelling. A common-sense knowledge base models and encodes knowledge about public-transport platforms and the actions and activities of passengers. Trajectory data from passengers is modelled as a time-series of human activities. Common-sense knowledge and rules are then applied to detect inconsistencies or errors in the data interpretation. Lastly, the rationality that characterises human behaviour is also captured here through a bottom-up Hierarchical Task Network planner that, along with common-sense, corrects misinterpretations to explain passenger behaviour. The system is validated using a simulated bus saloon scenario as a case-study. Eighteen video sequences were recorded with up to six passengers. Four metrics were used to evaluate performance. The system, with an accuracy greater than 90% for each of the four metrics, was found to outperform a rule-base system and a system containing planning alone.

Human Behavious Modelling for Discrete Event and Agent Based Simulation: A Case Study

This study is about the comparison of simulation techniques between Discrete Event Simulation (DES) and Agent Based Simulation (ABS). DES is one of the best-known types of simulation techniques in Operational Research. Recently, there has been an emergence of another technique, namely ABS. One of the qualities of ABS is that it helps to gain a better understanding of complex systems that involve the interaction of people with their environment as it allows to model concepts like autonomy and pro-activeness which are important attributes to consider. Although there is a lot of literature relating to DES and ABS, we have found none that focuses on exploring the capability of both in tackling the human behaviour issues which relates to queuing time and customer satisfaction in the retail sector. Therefore, the objective of this study is to identify empirically the differences between these simulation techniques by stimulating the potential economic benefits of introducing new policies in a department store. To apply the new strategy, the behaviour of consumers in a retail store will be modelled using the DES and ABS approach and the results will be compared. We aim to understand which simulation technique is better suited to human behaviour modelling by investigating the capability of both techniques in predicting the best solution for an organisation in using management practices. Our main concern is to maximise customer satisfaction, for example by minimising their waiting times for the different services provided.

Using intelligent agents to understand organisational behaviour

This paper introduces two ongoing research projects which seek to apply computer modelling techniques in order to simulate human behaviour within organisations. Previous research in other disciplines has suggested that complex social behaviours are governed by relatively simple rules which, when identified, can be used to accurately model such processes using computer technology. The broad objective of our research is to develop a similar capability within organisational psychology.

Modelling reactive and proactive behaviour in simulation

This research investigated the simulation model behaviour of a traditional and combined discrete event as well as agent based simulation models when modelling human reactive and proactive behaviour in human centric complex systems. A departmental store was chosen as human centric complex case study where the operation system of a fitting room in WomensWear department was investigated. We have looked at ways to determine the efficiency of new management policies for the fitting room operation through simulating the reactive and proactive behaviour of staff towards customers. Once development of the simulation models and their verification had been done, we carried out a validation experiment in the form of a sensitivity analysis. Subsequently, we executed a statistical analysis where the mixed reactive and proactive behaviour experimental results were compared with some reactive experimental results from previously published works. Generally, this case study discovered that simple proactive individual behaviour could be modelled in both simulation models. In addition, we found the traditional discrete event model performed similar in the simulation model output compared to the combined discrete event and agent based simulation when modelling similar human behaviour.

Using Research Methods in Human Computer Interaction to Design Technology for Resilience

Research in human computer interaction (HCI) covers both technological and human behavioural concerns. As a consequence, the contributions made in HCI research tend to be aware to either engineering or the social sciences. In HCI the purpose of practical research contributions is to reveal unknown insights about human behaviour and its relationship to technology. Practical research methods normally used in HCI include formal experiments, field experiments, field studies, interviews, focus groups, surveys, usability tests, case studies, diary studies, ethnography, contextual inquiry, experience sampling, and automated data collection. In this paper, we report on our experience using the evaluation methods focus groups, surveys and interviews and how we adopted these methods to develop artefacts: either interface’s design or information and technological systems. Four projects are examples of the different methods application to gather information about user’s wants, habits, practices, concerns and preferences. The goal was to build an understanding of the attitudes and satisfaction of the people who might interact with a technological artefact or information system. Conversely, we intended to design for information systems and technological applications, to promote resilience in organisations (a set of routines that allow to recover from obstacles) and user’s experiences. Organisations can here also be viewed within a system approach, which means that the system perturbations even failures could be characterized and improved. The term resilience has been applied to everything from the real estate, to the economy, sports, events, business, psychology, and more. In this study, we highlight that resilience is also made up of a number of different skills and abilities (self-awareness, creating meaning from other experiences, self-efficacy, optimism, and building strong relationships) that are a few foundational ingredients, which people should use along with the process of enhancing an organisation’s resilience. Resilience enhances knowledge of resources available to people confronting existing problems.

All in Good Time: Exploring Change in Neanderthal Behavioural Complexity

Since their discovery 150 years ago, Neanderthals have been considered incapable of behavioural change and innovation. Traditional synchronic approaches to the study of Neanderthal behaviour have perpetuated this view and shaped our understanding of their lifeways and eventual extinction. In this thesis I implement an innovative diachronic approach to the analysis of Neanderthal faunal extraction, technology and symbolic behaviour as contained in the archaeological record of the critical period between 80,000 and 30,000 years BP. The thesis demonstrates patterns of change in Neanderthal behaviour which are at odds with traditional perspectives and which are consistent with an interpretation of increasing behavioural complexity over time, an idea that has been suggested but never thoroughly explored in Neanderthal archaeology. Demonstrating an increase in behavioural complexity in Neanderthals provides much needed new data with which to fuel the debate over the behavioural capacities of Neanderthals and the first appearance of Modern Human Behaviour in Europe. It supports the notion that Neanderthal populations were active agents of behavioural innovation prior to the arrival of Anatomically Modern Humans in Europe and, ultimately, that they produced an early Upper Palaeolithic cultural assemblage (the Châtelperronian) independent of modern humans. Overall, this thesis provides an initial step towards the development of a quantitative approach to measuring behavioural complexity which provides fresh insights into the cognitive and behavioural capabilities of Neanderthals.