scholarly journals An Active Inference Approach to Dissecting Reasons for Non-Adherence to Antidepressants

2019 ◽  
Author(s):  
Ryan Smith ◽  
Sahib Khalsa ◽  
Martin Paulus
Keyword(s):  
Decision Making ◽  
Process Model ◽  
Time Course ◽  
Antidepressant Medication ◽  
Influential Factors ◽  
Active Inference ◽  
Individual Level ◽  
Markov Decision ◽  
Decision Making Processes ◽  
Partially Observable

AbstractBackgroundAntidepressant medication adherence is among the most important problems in health care worldwide. Interventions designed to increase adherence have largely failed, pointing towards a critical need to better understand the underlying decision-making processes that contribute to adherence. A computational decision-making model that integrates empirical data with a fundamental action selection principle could be pragmatically useful in 1) making individual level predictions about adherence, and 2) providing an explanatory framework that improves our understanding of non-adherence.MethodsHere we formulate a partially observable Markov decision process model based on the active inference framework that can simulate several processes that plausibly influence adherence decisions.ResultsUsing model simulations of the day-to-day decisions to take a prescribed selective serotonin reuptake inhibitor (SSRI), we show that several distinct parameters in the model can influence adherence decisions in predictable ways. These parameters include differences in policy depth (i.e., how far into the future one considers when deciding), decision uncertainty, beliefs about the predictability (stochasticity) of symptoms, beliefs about the magnitude and time course of symptom reductions and side effects, and the strength of medication-taking habits that one has acquired.ConclusionsClarifying these influential factors will be an important first step toward empirically determining which are contributing to non-adherence to antidepressants in individual patients. The model can also be seamlessly extended to simulate adherence to other medications (by incorporating the known symptom reduction and side effect trajectories of those medications), with the potential promise of identifying which medications may be best suited for different patients.

scholarly journals A Markov Decision Process Model for Traffic Prioritisation Provisioning

10.28945/2750 ◽  
2004 ◽  
Author(s):  
Abdullah Gani ◽  
Omar Zakaria ◽  
Nor Badrul Anuar Jumaat
Keyword(s):  
Decision Making ◽  
Markov Decision Process ◽  
Decision Process ◽  
Process Model ◽  
Decision Problems ◽  
Sequential Decision ◽  
Best Effort ◽  
Sequential Decision Problems ◽  
Markov Decision ◽  
Decision Making Processes

This paper presents an application of Markov Decision Process (MDP) into the provision of traffic prioritisation in the best-effort networks. MDP was used because it is a standard, general formalism for modelling stochastic, sequential decision problems. The implementation of traffic prioritisation involves a series of decision making processes by which packets are marked and classified before being despatched to destinations. The application of MDP was driven by the objective of ensuring the higher priority packets are not delayed by the lower ones. The MDP is believed to be applicable in improving the traffic prioritisation arbitration.

scholarly journals An analysis of systemic thinking in decision-making processes in the municipalities within the province of KwaZulu-Natal

2015 ◽  
Vol 4 (4) ◽  
pp. 531-547
Author(s):  
Mbuyiseni Goodlife Ntuli ◽  
Lawrence Mpela Lekhanya
Keyword(s):  
Decision Making ◽  
Process Model ◽  
Business Environment ◽  
Rational Decision ◽  
Systemic Thinking ◽  
Rational Decision Making ◽  
Theoretical Perspectives ◽  
Kwazulu Natal ◽  
Decision Making Processes ◽  
Decision Making Model

This paper advocates the adoption of systemic thinking in decision-making processes in municipalities. Most importantly, in this epoch of managing in complex and thought-provoking business environment, decision making is one of the most important skills required by any manager to remain effective. The success of a municipality or any business hinges on how well decisions are taken and implemented. In this paper, I intend to scrutinize decision making processes at strategic management levels in the municipalities within the province of KwaZulu-Natal. In doing that, a mixed method approach of qualitative and quantitative techniques was adopted in gathering data from sixty-one municipalities within the province of KwaZulu-Natal. This was done in order to substantiate theoretical perspectives from different erudite scholars on the discourse of systemic thinking in decision making processes. This notion of systemic thinking is coined upon the universally used rational decision making process model. Thus, the conceptualization of rational decision-making model was also considered in this paper, the possibility of decision failure, the complexity of the municipality, and systemic thinking as the recommended option of dealing with complexity was explored. The results indicates that the theory that underpins the adoption of systemic thinking in dealing with complexity today’s business environment is relevant.

Semi-Markov Decision-Making Processes with Vector Gains

1984 ◽  
Vol 28 (1) ◽  
pp. 191-193 ◽  
Author(s):  
T. M. Vinogradskaya ◽  
B. A. Geninson ◽  
A. A. Rubchinskii
Keyword(s):  
Decision Making ◽  
Markov Decision ◽  
Decision Making Processes

Cybersecurity Research: A Review of Current Research Topics

2018 ◽  
Vol 03 (04) ◽  
pp. 1850014 ◽  
Author(s):  
Yang Lu
Keyword(s):  
Systematic Review ◽  
Decision Making ◽  
Work Setting ◽  
Research Topics ◽  
Individual Level ◽  
Integrative Framework ◽  
Organization Level ◽  
R Project ◽  
Decision Making Processes ◽  
First Time

This paper presents a systematic review of empirical research on cybersecurity issues. 14 empirical articles about cybersecurity, published in the two top IS journals, MISQ (12) and ISR (2), between 2008 and 2017, were selected and analyzed, classified into three categories: individual level (non-work setting), employee level (work setting), and organization level (policy/regulation environment). This paper provides a holistic picture of cybersecurity issues, for instance, fundamental theories, impressive research methods, and influencing factors. More importantly, for the first time an integrative framework was developed by R Project, which potentially text-mines end-users’ behaviors and decision-making processes toward cybersecurity under the circumstance of security breach. Some explanations of extant empirical study and potential research are addressed and discussed as well.

(Re)Designing Business Processes Using Markov Theory and Constrained State, Transition and Actor Role Spaces

2019 ◽  
Vol 9 (2) ◽  
pp. 43-61 ◽  
Author(s):  
Sérgio Guerreiro
Keyword(s):  
Decision Making ◽  
Business Process ◽  
Business Processes ◽  
The Body ◽  
Process Redesign ◽  
Discount Factors ◽  
Body Of Knowledge ◽  
Markov Decision ◽  
Decision Making Processes ◽  
The Impact

Decision-making processes are the utmost important to steer the organizational change whenever business process workarounds are attempted during operational times. However, to decide the non-compliant situations, e.g., bypasses, social resistance, or collusion; the business manager demands contextualized and correct interpretations of the existing business process redesign options to cope with workarounds. This article explores the need to aid the decision-making process with a full constructional perspective to optimize the business processes redesign. So, the Markov decision process is combined with the body of knowledge of business processes, in specific, the concepts of designing enterprise-wide business transactions. This methodology supports the management initiatives with more knowledge about the value of business processes redesign. A classical chain of Order-to-Cash business processes (the order, the production, the distribution and the selling of goods) illustrate the benefits of this quantitative approach. Results obtained for business processes redesign in reaction to workarounds are reported. The analysis results show that this approach can anticipate the sub-optimal solutions before taking actions and highlights the impact of discount factors in the final obtained value. The contribution of this novel conceptual integration to the business processes community is the forecast of value function of business transaction redesign options when facing non-compliant workarounds. From related literature, business processes compliance usually comprises offline computation and the redesign is only considered in the forthcoming business processes instances. This article is innovative in the sense that it anticipates the value impact of a redesign, allowing more effective decisions to be taken.

Exploring Cognitive Decision-making Processes, Computer-focused Cyber Deviance Involvement and Victimization

2017 ◽  
Vol 54 (5) ◽  
pp. 639-679 ◽  
Author(s):  
Eric R. Louderback ◽  
Olena Antonaccio
Keyword(s):  
Decision Making ◽  
Negative Binomial ◽  
Negative Binomial Regression ◽  
Ordinary Least Squares ◽  
Sensitivity Analyses ◽  
Protective Effects ◽  
Individual Level ◽  
Older Employees ◽  
Decision Making Processes ◽  
Cognitive Decision

Objectives: Investigate the relationship between thoughtfully reflective decision-making (TRDM) and computer-focused cyber deviance involvement and computer-focused cybercrime victimization. Method: Survey data collected from samples of 1,039 employees and 418 students at a large private university were analyzed using ordinary least squares and negative binomial regression to test the effects of TRDM on computer-focused cyber deviance involvement and victimization. Results: TRDM reduces computer-focused cyber deviance involvement and computer-focused cybercrime victimization across measures and samples. The sensitivity analyses also indicated that TRDM is a more robust predictor of cyber deviance involvement than victimization. The results from moderation analyses showed that, whereas protective effects of TRDM are invariant across genders, they are less salient among older employees for the scenario-based measure of cybercrime victimization. Conclusions: Individual-level cognitive decision-making processes are important in predicting computer-focused cyber deviance involvement and victimization. These results can inform the development of targeted institutional and criminal justice policies aimed at reducing computer-focused cybercrime.

scholarly journals Decision Making in Complex Multiagent Contexts: A Tale of Two Frameworks

AI Magazine ◽  
2012 ◽  
Vol 33 (4) ◽  
pp. 82 ◽  
Author(s):  
Prashant J. Doshi
Keyword(s):  
Decision Making ◽  
Markov Decision Process ◽  
Decision Process ◽  
Partial Information ◽  
Autonomous Systems ◽  
Relevant Research ◽  
Physical Context ◽  
Markov Decision ◽  
Partially Observable Markov ◽  
Partially Observable

Decision making is a key feature of autonomous systems. It involves choosing optimally between different lines of action in various information contexts that range from perfectly knowing all aspects of the decision problem to having just partial knowledge about it. The physical context often includes other interacting autonomous systems, typically called agents. In this article, I focus on decision making in a multiagent context with partial information about the problem. Relevant research in this complex but realistic setting has converged around two complementary, general frameworks and also introduced myriad specializations on its way. I put the two frameworks, decentralized partially observable Markov decision process (Dec-POMDP) and the interactive partially observable Markov decision process (I-POMDP), in context and review the foundational algorithms for these frameworks, while briefly discussing the advances in their specializations. I conclude by examining the avenues that research pertaining to these frameworks is pursuing.

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