The Optimality of Decision Making During Motor Learning

In our daily lives, we often must predict how well we are going to perform in the future based on an evaluation of our current performance and an assessment of how much we will improve with practice. Such predictions can be used to decide whether to invest our time and energy in learning and, if we opt to invest, what rewards we may gain. This thesis investigated whether people are capable of tracking their own learning (i.e. current and future motor ability) and exploiting that information to make decisions related to task reward. In experiment one, participants performed a target aiming task under a visuomotor rotation such that they initially missed the target but gradually improved. After briefly practicing the task, they were asked to select rewards for hits and misses applied to subsequent performance in the task, where selecting a higher reward for hits came at a cost of receiving a lower reward for misses. We found that participants made decisions that were in the direction of optimal and therefore demonstrated knowledge of future task performance. In experiment two, participants learned a novel target aiming task in which they were rewarded for target hits. Every five trials, they could choose a target size which varied inversely with reward value. Although participants’ decisions deviated from optimal, a model suggested that they took into account both past performance, and predicted future performance, when making their decisions. Together, these experiments suggest that people are capable of tracking their own learning and using that information to make sensible decisions related to reward maximization.

Design and Implementation of a Low Cost Virtual Rugby Decision Making Interactive

The paper describes the design and implementation of a novel low cost virtual rugby decision making interactive for use in a visitor centre. Original laboratory-based experimental work in decision making in rugby, using a virtual reality headset [1] is adapted for use in a public visitor centre, with consideration given to usability, costs, practicality and health and safety. Movement of professional rugby players was captured and animated within a virtually recreated stadium. Users then interact with these virtual representations via use of a lowcost sensor (Microsoft Kinect) to attempt to block them. Retaining the principles of perception and action, egocentric viewpoint, immersion, sense of presence, representative design and game design the system delivers an engaging and effective interactive to illustrate the underlying scientific principles of deceptive movement. User testing highlighted the need for usability, system robustness, fair and accurate scoring, appropriate level of difficulty and enjoyment.

Exercise Prescription for Patients with Non-specific Chronic Low Back Pain: a Qualitative Study of Patients' Experiences in Decision Making

Background The culture of current clinical practice calls for collaboration between therapists and patients, sharing power and responsibility. This paper reports on the findings of a qualitative study of exercise prescription for patients with NSCLBP, taking into account issues such as decision making and how this accords with patient preferences and experiences. Objective To understand the treatment decision making experiences, information and decision support needs of patients with NSCLBP who have been offered exercise as part of their management plan. Design A qualitative study using a philosophical hermeneutic approach. Methods Semi-structured interviews with eight patients (including use of brief patient vignettes) was undertaken to explore their personal experiences of receiving exercise as part of the management of their NSCLBP, and their involvement in decisions regarding their care. Findings The findings provide a detailed insight into patients’ perceptions and experiences of receiving exercise-based management strategies. Four themes were formed from the texts: (1) patients’ expectations and patients’ needs are not synonymous, (2) information is necessary but often not sufficient, (3) not all decisions need to be shared, and (4) wanting to be treated as an individual. Conclusions Shared decision making did not appear to happen in physiotherapy clinical practice, but equally may not be what every patient wants. The overall feeling of the patients was that the therapist was dominant in structuring the interactions, leaving the patients feeling disempowered to question and contribute to the decision making.

Decision-making process in Portuguese Erasmus student mobility: case study

With the evolution of nowadays knowledge-based economies, the labour class becomes more competitive. As a way of getting skills that bring benefits to their careers, university students take advantage of the many opportunities available and go abroad to study. This study develops and empirically tests a structural model that examines the antecedents that influence the decision-making process of an Erasmus student under mobility for studies (EMS) in Aveiro, Coimbra and Porto (2014-2015). Reliability analysis, exploratory factor analysis and linear regressions were used to evaluate the model. Based on a survey with a sample of 872 valid responses, this study has demonstrated that EMS students are also influenced by touristic factors, which gives support to what has recently been approached by other authors. Conclusions and suggestions can be applied by other organizations, mainly Higher Education Institutions in order to attract more EMS students.

Natural Language Generation enhances human decision-making with uncertain information.

Decision-making is often dependent on uncertain data, e.g. data associated with confidence scores or probabilities. We present a comparison of different informa- tion presentations for uncertain data and, for the first time, measure their effects on human decision-making. We show that the use of Natural Language Genera- tion (NLG) improves decision-making un- der uncertainty, compared to state-of-the- art graphical-based representation meth- ods. In a task-based study with 442 adults, we found that presentations using NLG lead to 24% better decision-making on av- erage than the graphical presentations, and to 44% better decision-making when NLG is combined with graphics. We also show that women achieve significantly better re- sults when presented with NLG output (an 87% increase on average compared to graphical presentations).

Understanding information use in multiattribute decision making

An inference task in one in which some known set of information is used to produce an estimate about an unknown quantity. Existing theories of how humans make inferences include specialized heuristics that allow people to make these inferences in familiar environments quickly and without unnecessarily complex computation. Specialized heuristic processing may be unnecessary, however; other research suggests that the same patterns in judgment can be explained by existing patterns in encoding and retrieving memories. This dissertation compares and attempts to reconcile three alternate explanations of human inference. After justifying three hierarchical Bayesian version of existing inference models, the three models are com- pared on simulated, observed, and experimental data. The results suggest that the three models capture different patterns in human behavior but, based on posterior prediction using laboratory data, potentially ignore important determinants of the decision process.

Combined Machine Learning Techniques for Decision Making Support in Medicine

Computational intelligent support for decision making is becoming increasingly popular and essential among medical professionals. Also, with the modern medical devices being capable to communicate with ICT, created models can easily find practical translation into software. Machine learning solutions for medicine range from the robust but opaque paradigms of support vector machines and neural networks to the also performant, yet more comprehensible, decision trees and rule-based models. So how can such different techniques be combined such that the professional obtains the whole spectrum of their particular advantages? The presented approaches have been conceived for various medical problems, while permanently bearing in mind the balance between good accuracy and understandable interpretation of the decision in order to truly establish a trustworthy ‘artificial’ second opinion for the medical expert.

Computational approaches to emotional decision making

Findings on the role that emotion plays in human behavior have transformed Artificial Intelligence computations. Modern research explores how to simulate more intelligent and flexible systems. Several studies focus on the role that emotion has in order to establish values for alternative decision and decision outcomes. For instance, Busemeyer et al. (2007) argued that emotional state affects the subjectivity value of alternative choice. However, emotional concepts in these theories are generally not defined formally and it is difficult to describe in systematic detail how processes work. In this sense, structures and processes cannot be explicitly implemented. Some attempts have been incorporated into larger computational systems that try to model how emotion affects human mental processes and behavior (Becker-Asano & Wachsmuth, 2008; Marinier, Laird & Lewis, 2009; Marsella & Gratch, 2009; Parkinson, 2009; Sander, Grandjean & Scherer, 2005). As we will see, some tutoring systems have explored this potential to inform user models. Likewise, dialogue systems, mixed-initiative planning systems, or systems that learn from observation could also benefit from such an approach (Dickinson, Brew & Meurers, 2013; Jurafsky & Martin, 2009). That is, considering emotion as interaction can be relevant in order to explain the dynamic role it plays in action and cognition (see Boehner et al., 2007).

Twelve Certain Men: The Impact of Emotional Appraisals on Juror Decision-Making

Our jury system is predicated upon the expectation that jurors engage in systematic processing when considering evidence and making decisions. They are instructed to interpret facts and apply the appropriate law in a fair, dispassionate manner, free of all bias, including that of emotion. However, emotions containing an element of certainty (e.g., anger and happiness, which require little cognitive effort in determining their source) can often lead people to engage in superficial, heuristic-based processing. Compare this to uncertain emotions (e.g., hope and fear, which require people to seek out explanations for their emotional arousal), which instead has the potential to lead them to engage in deeper, more systematic processing. The purpose of the current research is in part to confirm past research (Tiedens & Linton, 2001; Semmler & Brewer, 2002) that uncertain emotions (like fear) can influence decision-making towards a more systematic style of processing, whereas more certain emotional states (like anger) will lead to a more heuristic style of processing. Studies One, Two, and Three build upon this prior research with the goal of improving methodological rigor through the use of film clips to reliably induce emotions, with awareness of testimonial details serving as measures of processing style. The ultimate objective of the current research was to explore this effect in Study Four by inducing either fear, anger, or neutral emotion in mock jurors, half of whom then followed along with a trial transcript featuring eight testimonial inconsistencies, while the other participants followed along with an error-free version of the same transcript. Overall rates of detection for these inconsistencies was expected to be higher for the uncertain/fearful participants due to their more effortful processing compared to certain/angry participants. These expectations were not fulfilled, with significant main effects only for the transcript version (with or without inconsistencies) on overall inconsistency detection rates. There are a number of plausible explanations for these results, so further investigation is needed.

Enabling effective operational decision making on a Combined Heat and Power System using the 5C architecture

The use of Cyber Physical Systems (CPS) to optimise industrial energy systems is an approach which has the potential to positively impact on manufacturing sector energy efficiency. The need to obtain data to facilitate the implementation of a CPS in an industrial energy system is however a complex task which is often implemented in a non-standardised way. The use of the 5C CPS architecture has the potential to standardise this approach. This paper describes a case study where data from a Combined Heat and Power (CHP) system located in a large manufacturing company was fused with grid electricity and gas models as well as a maintenance cost model using the 5C architecture with a view to making effective decisions on its cost efficient operation. A control change implemented based on the cognitive analysis enabled via the 5C architecture implementation has resulted in energy cost savings of over €7400 over a four-month period, with energy cost savings of over €150,000 projected once the 5C architecture is extended into the production environment.

The environmental DNA in the risk assessment and decision making processes for the invasive species management in agri-food sector, hydraulic security and biodiversity conservation

The use of environmental DNA (eDNA) analysis as a monitoring tool is becoming more and more widespread. The eDNA metabarcoding methods allow rapid community assessments of different target taxa. This work is focused on the validation of the environmental DNA metabarcoding protocol for biodiversity assessment of freshwater habitats. Scolo Dosolo was chosen as study area and three sampling points were defined for traditional and eDNA analyses. The gutter is a 205 m long anthropic canal located in Sala Bolognese (Bologna, Italy). Fish community and freshwater invertebrate metazoans were the target groups for the analysis. After a preliminary study in summer 2019, 2020 was devoted to the sampling campaign with winter (January), spring (May), summer (July) and autumn (October) surveys. Alongside with the water samplings for the eDNA study, also traditional fish surveys using the electrofishing technique were performed to assess fish community composition; census on invertebrates was performed using an entomological net and a surber sampler. After in silico analysis, the MiFish primer set amplifying a fragment of the 12s rRNA gene was selected for bony fishes. For invertebrates the FWHF2 + FWHR2N primer combination, that amplifies a region of the mitochondrial coi gene, was chosen. Raw reads were analyzed through a bioinformatic pipeline based on OBITools metabarcoding programs package and QIIME2. The OBITools pipeline retrieved seven fish taxa and 54 invertebrate taxa belonging to six different phyla, while QIIME2 recovered eight fish taxa and 45 invertebrate taxa belonging to the same six phyla as the OBITools pipeline. The metabarcoding results were then compared with the traditional surveys data and bibliographic records. Overall, the validated protocol provides a reliable picture of the biodiversity of the study area and an efficient support to the traditional methods.

Circumplex Model to analyze the impact of emotions on decision-making processes in innovation management

Group work allows participants to pool their thoughts and examine difficulties from several angles. In these settings, it is possible to attempt things that an individual could not achieve, combining a variety of abilities and knowledge to tackle more complicated and large-scale challenges. That’s why nowadays collaborative work is becoming more and more widespread to solve complex innovation dilemmas. Since innovation isn’t a tangible thing, most innovation teams used to take decisions based on performance KPIs such as forecasted engagement, projected profitability, investments required, cultural impacts etc. Have you ever wondered the reason why sometimes innovation group processes come out with decisions which are not the optimal meeting point of all the KPIs? Has this decision been influenced by other factors? Some researchers account part of this phenomenon to the emotions in group-based interaction between participants. I will develop a literature review that is split into three parts: first, I will consider some emotions theories from an individual perspective; secondly, a wider view of collective interactions theories will be provided; lastly, I will supply some recent collective interaction empirical studies. After the theoretical and empirical gaps have been tackled, the study will additionally move forward with a methodological point of view, about the Circumplex Model, which is the model I used to evaluate emotions in my research. This model has been applied to SUGAR project, which is the biggest design thinking academy worldwide.

Information from managing information systems as a fundamental element to support decision-making in hospitals

This article deals with the activity of defining information of hospital systems as fundamental for choosing the type of information systems to be used and also the organizational level to be supported. The use of hospital managing information systems improves the user`s decision -making process by allowing control report generation and following up the procedures made in the hospital as well.

Decision making in fuzzy environment and multicriteria power engineering problems

This paper presents results of research into the use of the Bellman-Zadeh approach to decision making in a fuzzy environment for solving multicriteria power engineering problems. The application of the approach conforms to the principle of guaranteed result and provides constructive lines in computationally effective obtaining harmonious solutions on the basis of solving associated maxmin problems. The presented results are universally applicable and are already being used to solve diverse classes of power engineering problems. It is illustrated by considering problems of power and energy shortage allocation, power system operation, optimization of network configuration in distribution systems, and energetically effective voltage control in distribution systems. (c) 2011 Elsevier Ltd. All rights reserved.