Software agents & human behavior

People make important decisions in emergencies. Often these decisions involve high stakes in terms of lives and property. Bhopal disaster (1984), Piper Alpha disaster (1988), Montara blowout (2009), and explosion on Deepwater Horizon (2010) are a few examples among many industrial incidents. In these incidents, those who were in-charge took critical decisions under various ental stressors such as time, fatigue, and panic. This thesis presents an application of naturalistic decision-making (NDM), which is a recent decision-making theory inspired by experts making decisions in real emergencies. This study develops an intelligent agent model that can be programed to make human-like decisions in emergencies. The agent model has three major components: (1) A spatial learning module, which the agent uses to learn escape routes that are designated routes in a facility for emergency evacuation, (2) a situation recognition module, which is used to recognize or distinguish among evolving emergency situations, and (3) a decision-support module, which exploits modules in (1) and (2), and implements an NDM based decision-logic for producing human-like decisions in emergencies. The spatial learning module comprises a generalized stochastic Petri net-based model of spatial learning. The model classifies routes into five classes based on landmarks, which are objects with salient spatial features. These classes deal with the question of how difficult a landmark turns out to be when an agent observes it the first time during a route traversal. An extension to the spatial learning model is also proposed where the question of how successive route traversals may impact retention of a route in the agent’s memory is investigated. The situation awareness module uses Markov logic network (MLN) to define different offshore emergency situations using First-order Logic (FOL) rules. The purpose of this module is to give the agent the necessary experience of dealing with emergencies. The potential of this module lies in the fact that different training samples can be used to produce agents having different experience or capability to deal with an emergency situation. To demonstrate this fact, two agents were developed and trained using two different sets of empirical observations. The two are found to be different in recognizing the prepare-to-abandon-platform alarm (PAPA ), and similar to each other in recognition of an emergency using other cues. Finally, the decision-support module is proposed as a union of spatial-learning module, situation awareness module, and NDM based decision-logic. The NDM-based decision-logic is inspired by Klein’s (1998) recognition primed decision-making (RPDM) model. The agent’s attitudes related to decision-making as per the RPDM are represented in the form of belief, desire, and intention (BDI). The decision-logic involves recognition of situations based on experience (as proposed in situation-recognition module), and recognition of situations based on classification, where ontological classification is used to guide the agent in cases where the agent’s experience about confronting a situation is inadequate. At the planning stage, the decision-logic exploits the agent’s spatial knowledge (as proposed in spatial-learning module) about the layout of the environment to make adjustments in the course of actions relevant to a decision that has already been made as a by-product of situation recognition. The proposed agent model has potential to be used to improve virtual training environment’s fidelity by adding agents that exhibit human-like intelligence in performing tasks related to emergency evacuation. Notwithstanding, the potential to exploit the basis provided here, in the form of an agent representing human fallibility, should not be ignored for fields like human reliability analysis

An Examination of the Decision-Making Process Instructional Designers Use to Complete Projects With the Constraints of Limited Time and Tools

Based on a phenomenological theoretical perspective, the purpose of this qualitative study was to explore how instructional designers make decisions related to determining which layers and related instructional design activities to address based on time and tool resource constraints. To explore the topic, this study was guided by five research questions which included: (a) what type of time and tool constraints do instructional design practitioners experience, (b) how do instructional design practitioners make decisions based on time constraints when completing work projects, (c) how do instructional design practitioners make decisions based on tool constraints when completing work projects, (d) how do instructional design practitioners determine which layers or questions to address given project constraints such as time and tool limitations, and (e) what steps do instructional design practitioners omit during work projects that have time and or/tool constraints? The study included 20 instructional designers (n=20) that work in various industries including higher education institutions, consulting, tourism, charity/nonprofit, health care, government, and retail. There were a total 14 female participants and 6 male participants. Upon the completion of 20 interviews and analysis of interview notes, six themes and three patterns emerged. The findings from this study show that in response to the constraint of limited time to design, develop, and implement instructional interventions, instructional designers modify instructional design processes that are based on traditional instructional design models. The findings suggested that when faced with tool constraints, instructional designers found ways to “figure it out” and worked within the constraints of the tools. The findings also highlighted that instructional designers reference prior knowledge and similar past projects in order to make decisions throughout the design process

A Study of Decision Making in British Business Improvement District Organisations

The British BID industry has been growing rapidly since the passing of the BID legislation in the year 2004 by the UK government. BID organisations are known for the ability to generate private funds for the purpose of supporting local councils in the development of town and city centres in the UK. The vast literature on BID however has been on issues such as the evaluation of BID organisations, the undemocratic nature of BIDs, and the impact of BID organisations in communities paying less attention to how BID organisations make place-based decisions that are vital to their host communities. This research explores the BID industry in the UK from the lens of organisational behaviour and identifies the determinants of decision-making within BID organisations, as well as how BID organisations manage the different stakeholder groups participating in the governance of places. Case study methodology was to examine decision-making in four BID cases. Findings from the study suggest that there are three determinants of decision-making used by BID organisations: Funding, BID governance, and Nature of Projects. BID organisations engage with stakeholder using a tactics known as Enrolment. Through enrolment, BID organisations inform, consult, collaborate, and empower their stakeholders to get involved in their decision-making process. A decision-making framework for understanding Place-Based Decision-Making (PBDM) among BID organisations is proposed based on the findings of this study. The framework maps out the steps in making decisions by BID organisations. Contributions arising from this research are: The strategy used by BID organisations in engaging their diverse stakeholder groups, a framework illustrating the decision-making phases in BID organisations