Multi-alternative Decision Research Articles

A Sequential Sampling Approach to the Integration of Habits and Goals

Habits often conflict with goal-directed behaviors and this phenomenon continues to attract interests from neuroscientists, experimental psychologists, and applied health psychologists. Recent computational models explain habit-goal conflicts as the competitions between two learning systems, arbitrated by a central unit. Based on recent research that combined reinforcement learning and sequential sampling, we show that habit-goal conflicts can be more parsimoniously explained by a dynamic integration of habit and goal values in a sequential sampling model, without any arbitration. A computational model was developed by extending the multialternative decision field theory with the assumptions that habits bias starting points of preference accumulation, and that goal importance and goal relevance determine sampling probabilities of goal-related attributes. Simulation studies demonstrated our approach’s ability to qualitatively reproduce important empirical findings from three paradigms – classic devaluation, devaluation with a concurrent schedule, and reversal learning, and to predict gradual changes in decision times. In addition, a parameter recovery exercise using approximate Bayesian computation showcased the possibility of fitting the model to empirical data in future research. Implications of our work for habit theories and applications are discussed.

SISTEM PENDUKUNG KEPUTUSAN PEMILIHAN LOKASI CAMPING BERDASARKAN KESULITAN TRACK DI SUMATERA UTARA DENGAN MENGGUNAKAN METODE TOPSIS

In the selection of camping sites and hiking areas, a system that could be used to help in the process of choosing a camping site with some criteria, a budget ora budget, a number of people, a certain amount of time to spend, as well as the altitude of MDPL, the humidity of a field, and a camping site. The system is built using the latter method for others, solutions for others to be identical to the ideal solution (topsis) category, the multi-alternative decision making (MCDM), which is the technique of several available alternative options for establishing the best alternatives, particularly multi, making decision (madm) in the problem-solving process that it hopes will help and support for making decisions made by decision-makers. The selection of outdoor tools and results from this system will be a list of reports of outdoor equipment for camping and hiking that match the camping site. The system will later produce results of outdoor equipment and any preparations to make camp.

Doubts about the reproducibility of the similarity effect in multialternative decision making

Doubts about the reproducibility of the similarity effect in multialternative decision making

Effects of different cognitive processing on the occurrence of Choice Blindness in multi-alternative decision making

Effects of different cognitive processing on the occurrence of Choice Blindness in multi-alternative decision making

Optimal Allocation of Finite Sampling Capacity in Accumulator Models of Multialternative Decision Making.

When facing many options, we narrow down our focus to very few of them. Although behaviors like this can be a sign of heuristics, they can actually be optimal under limited cognitive resources. Here, we study the problem of how to optimally allocate limited sampling time to multiple options, modeled as accumulators of noisy evidence, to determine the most profitable one. We show that the effective sampling capacity of an agent increases with both available time and the discriminability of the options, and optimal policies undergo a sharp transition as a function of it. For small capacity, it is best to allocate time evenly to exactly five options and to ignore all the others, regardless of the prior distribution of rewards. For large capacities, the optimal number of sampled accumulators grows sublinearly, closely following a power law as a function of capacity for a wide variety of priors. We find that allocating equal times to the sampled accumulators is better than using uneven time allocations. Our work highlights that multialternative decisions are endowed with breadth–depth tradeoffs, demonstrates how their optimal solutions depend on the amount of limited resources and the variability of the environment, and shows that narrowing down to a handful of options is always optimal for small capacities.

Metode Multi Attributive Border Approximation Area Comparison (MABAC) Untuk Penilaian Kinerja Dalam Pengelolaan Alokasi Dana Desa (ADD)

The Village Fund Allocation is one income proceed for the Village Revenue and Expenditure Budget of the rural government. For the implementation of financial governance, the Department of Community and Rural Empowerment does not yet have a performance appraisal system in managing the Fund Allocations. The Performance Appraisal System which is developed in this study aims to determine the optimality of rural governments in managing the Village Fund Allocation. The research methodology used in the study is MABAC (Multi-Attributive Border Approximation Area Comparison), a multi-alternative decision type. This method was chosen because of its stability and consistency in the solutions of decision making, compared to other decision support methods. The study was carried out on 11 villages with predetermined criteria data. From this data, an analysis is carried out resulting in values of performance assessment as well as the optimality of Fund Management.

Faktor - Faktor Pendukung Keputusan Rujukan Pasien pada Fasilitas Kesehatan Tingkat Pertama (FKTP) dengan metode Analytical Hierrarchy Process (AHP)

Pratama Bakti Timah Clinic is one of the First Level Health Facilities (FKTP) that provides health services to the community in the Pangkalpinang area and its surroundings. In these health service activities, when a patient requires special medical care in terms of medical services, medical personnel, medical support, outpatient services, and inpatient services, the patient will be referred to a higher health facility. Considering the various factors that cause patients to be referred and there are several hospitals that are referred to, this condition is a multi-criteria and multi-alternative condition. To overcome this, it is necessary to design a decision support system that will make it easier for medical administration service officers at the Primary Clinic. The decision support system is designed using the Analytical Hierarchy Process (AHP) method which is able to accommodate multi-criteria and multi-alternative decision making. The results of data processing showed that the most important factor in the referral of FKTP patients at the Pratama Clinic was the outpatient service factor with a weight of 30.7%, the second factor was medical services 24.4%, the third factor was medical personnel 17.5%, the fourth factor was supporting medical services 15.9%, and the last is inpatient services 11.4%. While the first referral hospital is RSUD Ir. Soekarno with a weight of 31.1%, then Depati Hamzah Hospital with a weight of 27.5%, then Bakti Timah Hospital with 27.3%, and Bakti Wara Hospital with 14.1%.

A process-oriented probabilistic linguistic decision-making model with unknown attribute weights

As an effective tool to describe qualitative evaluations, probabilistic linguistic term set (PLTS) can identify the different preference degrees for the possible linguistic evaluations. For the multi-attribute decision making (MADM) problems based on the PLTSs, making decisions is not instantaneous behavior but needs some time to complete information processing. Considering the dynamic nature of decision-making behavior, this study aims to develop a process-oriented probabilistic linguistic decision-making framework. First, we introduce the parameters in the probabilistic linguistic multi-alternative decision field theory (PLMDFT) model. An improved decision rule for selecting the optimal alternative(s) is also presented. Then, a deviation entropy-based model is developed to determine attribute weights. Furthermore, we construct a probabilistic linguistic decision-making framework based on the PLMDFT and deviation entropy. Finally, the constructed framework is applied to solve emergency scheme selection problem. Some discussion and comparative analysis is complemented to demonstrate the validity of the proposed framework.

Influence of divided attention on the attraction effect in multialternative choice

AbstractThe attraction effect in multialternative decision making reflects the context-dependent violation of rational choice axioms. This study examined the effect of concurrent divided attention in three-alternative visual choice tasks. The concurrent divided attention task is considered to consume the mental resources available for the choice task. There were three conditions: (a) the task-relevant condition, in which the auditory task should consume resources across multiple levels; (b) the task-irrelevant condition, in which the auditory stimuli should consume perceptual resources; (c) and the control condition, in which the resources should not be consumed by auditory stimuli. Thirty-three participants solved 24 hypothetical purchase problems with three alternatives that differed in terms of two attributes. The results indicated that the choice proportion of the target was significantly higher in the task-relevant condition than in the task-irrelevant and control conditions, thereby suggesting that a reduction in cognitive (and/or response) resources is critical for the attraction effect.

Bayesian Semiparametric Longitudinal Drift-Diffusion Mixed Models for Tone Learning in Adults

Understanding how adult humans learn nonnative speech categories such as tone information has shed novel insights into the mechanisms underlying experience-dependent brain plasticity. Scientists have traditionally examined these questions using longitudinal learning experiments under a multi-category decision making paradigm. Drift-diffusion processes are popular in such contexts for their ability to mimic underlying neural mechanisms. Motivated by these problems, we develop a novel Bayesian semiparametric inverse Gaussian drift-diffusion mixed model for multi-alternative decision making in longitudinal settings. We design a Markov chain Monte Carlo algorithm for posterior computation. We evaluate the method’s empirical performances through synthetic experiments. Applied to our motivating longitudinal tone learning study, the method provides novel insights into how the biologically interpretable model parameters evolve with learning, differ between input-response tone combinations, and differ between well and poorly performing adults. Supplementary materials for this article, including a standardized description of the materials available for reproducing the work, are available as an online supplement.

A time-series saccades analysis of the attraction and compromise effects based on the final decision in multialternative decision making

A time-series saccades analysis of the attraction and compromise effects based on the final decision in multialternative decision making

Heuristics and optimal solutions to the breadth–depth dilemma

In multialternative risky choice, we are often faced with the opportunity to allocate our limited information-gathering capacity between several options before receiving feedback. In such cases, we face a natural trade-off between breadth-spreading our capacity across many options-and depth-gaining more information about a smaller number of options. Despite its broad relevance to daily life, including in many naturalistic foraging situations, the optimal strategy in the breadth-depth trade-off has not been delineated. Here, we formalize the breadth-depth dilemma through a finite-sample capacity model. We find that, if capacity is small (∼10 samples), it is optimal to draw one sample per alternative, favoring breadth. However, for larger capacities, a sharp transition is observed, and it becomes best to deeply sample a very small fraction of alternatives, which roughly decreases with the square root of capacity. Thus, ignoring most options, even when capacity is large enough to shallowly sample all of them, is a signature of optimal behavior. Our results also provide a rich casuistic for metareasoning in multialternative decisions with bounded capacity using close-to-optimal heuristics.

Framing context effects with reference points

Research on reference points highlights how alternatives outside the choice set can alter the perceived value of available alternatives, arguably framing the choice scenario. The present work utilizes reference points to study the effects of framing in preferential choice, using the similarity and attraction context effects as performance measures. We specifically test the predictions of Multialternative Decision by Sampling (MDbS; Noguchi & Stewart, 2018), a recent preferential choice model that can account for both reference points and context effects. In Experiment 1, consistent with predictions by MDbS, we find a standard similarity effect when no reference point is given that increases when both dimensions are framed negatively and decreases when both dimensions are framed positively. Contrary to predictions by MDbS, when the two dimensions are framed as tradeoffs, participants prefer whichever alternative performs best in the negatively framed dimension. Performance of MDbS was improved by the addition of a frame-based global attention allocation mechanism. Experiment 2 extends these results to a “by-dimension” presentation format in an attempt to bring participant behavior in line with MDbS assumptions. The empirical and modeling results replicated those of Experiment 1. Experiment 3 used the attraction effect to test the effects of framing when the best-performing alternative on each dimension was identical across target conditions, therefore reducing the potential effects of a global attention allocation mechanism. The effects of framing were indeed greatly reduced, and the performance of MDbS was markedly improved. The results extend framing to the context effects literature, provide new benchmarks for models and theories of context effects, and point to the need for a global attention mechanism.

Similarity, Attraction, and Compromise Effects: Original Findings, Recent Empirical Observations, and Computational Cognitive Process Models

Abstract Preference reversals—a decision maker prefers A over B in one situation but B over A in another—demonstrate that human behavior violates invariance assumptions of (utility-based) rational choice theories. In the field of multi-alternative multi-attribute decision-making research, 3 preference reversals received special attention: similarity, attraction, and compromise effects. The 3 so-called context effects are changes in (relative) choice probabilities for 2 choice alternatives after a third “decoy” option is added to the set. Despite their simplicity, the effects demonstrate that choice probabilities in multi-alternative decision making are contingent on the local context, that is, on the choice set under consideration. Because of their simplicity, on the other hand, similarity, attraction, and compromise effects have been successfully examined in numerous studies to date, and they have become of increasing interest for differentiating between computational cognitive process models of multi-alternative multi-attribute decision making. However, the stimulus arrangement for producing the effects seems to vary between studies, which becomes challenging when model accounts are compared. The purpose of this review is to present various paradigms in a coherent way and describe various model accounts based on a common structure.

HFLTS-TOPSIS With Pseudo-distance in Determining The Best Lecturers

Decision making is sometimes faced with a situation where assessment is given in the form of linguistic variables, which have a certain range of values so that decision making cannot be given in the form of numerical values. One approach commonly used is Hesitant Fuzzy Linguistic Term Sets (HFLTS) which is a multi-criteria and multi-alternative decision making method. In TOPSIS which has the concept of distance measurement, basically the chosen one is the best alternative is an alternative that has the closest distance to a positive solution and the farthest distance with a negative solution. The incorporation of HFLTS-TOPSIS has the advantage that decision making can be done in the form of variable linguistics and also a situation where there are benefit criteria and cost criteria. This study will use the HFLTS-TOPSIS approach that has been modified in the distance calculation section so that distance calculation is based on the difference of preference degree between the two HFLTS. The results of research conducted by a number of researchers show that using pseudo-distance will provide advantages compared to the standard HLFTS-TOPSIS. Pseudo-distance HFLTS-TOPSIS will be applied in the selection of the best lecturers. The criteria used in this study are: Student Satisfaction, Research, Number of late, and number of complaints from students.

Optimal policy for multi-alternative decisions.

Everyday decisions frequently require choosing among multiple alternatives. Yet the optimal policy for such decisions is unknown. Here we derive the normative policy for general multi-alternative decisions. This strategy requires evidence accumulation to nonlinear, time-dependent bounds that trigger choices. A geometric symmetry in those boundaries allows the optimal strategy to be implemented by a simple neural circuit involving normalization with fixed decision bounds and an urgency signal. The model captures several key features of the response of decision-making neurons as well as the increase in reaction time as a function of the number of alternatives, known as Hick's law. In addition, we show that in the presence of divisive normalization and internal variability, our model can account for several so-called 'irrational' behaviors, such as the similarity effect as well as the violation of both the independence of irrelevant alternatives principle and the regularity principle.

Effortful Processing Reduces the Attraction Effect in Multi-Alternative Decision Making: An Electrophysiological Study Using a Task-Irrelevant Probe Technique.

The attraction effect in multi-alternative decision making reflects the context-dependent violation of axioms that are considered fundamental to rational choice. This effect is believed to depend on relatively effortless and intuitive processing (System 1) rather than on effortful and elaborative processing (System 2). To investigate the relationship between cognitive resources and the attraction effect in detail, we used a task-irrelevant probe technique, wherein task-irrelevant auditory probes were presented while participants viewed each alternative in a decision-making task, and measured the electroencephalographic responses to the probes. Thirty participants solved 48 hypothetical purchase problems with three alternatives that differed in terms of two attributes. We found that, in the second epoch of the experimental trials (possibly corresponding to the evaluation and comparison stage), the mean N1 amplitudes of the event-related potentials elicited by the auditory probes were significantly smaller when participants chose the competitor (i.e., trials in which no attraction effect occurred) than when participants chose the target (i.e., trials in which an attraction effect may have occurred). This result suggests that the allocation of more cognitive resources to the alternatives disrupts the attraction effect. This finding supports the assumption that intuitive comparisons among alternatives executed by System 1 are critical for the occurrence of the attraction effect.

Response-time data provide critical constraints on dynamic models of multi-alternative, multi-attribute choice.

Understanding the cognitive processes involved in multi-alternative, multi-attribute choice is of interest to a wide range of fields including psychology, neuroscience, and economics. Prior investigations in this domain have relied primarily on choice data to compare different theories. Despite numerous such studies, results have largely been inconclusive. Our study uses state-of-the-art response-time modeling and data from 12 different experiments appearing in six different published studies to compare four previously proposed theories/models of these effects: multi-alternative decision field theory (MDFT), the leaky-competing accumulator (LCA), the multi-attribute linear ballistic accumulator (MLBA), and the associative accumulation model (AAM). All four models are, by design, dynamic process models and thus a comprehensive evaluation of their theoretical properties requires quantitative evaluation with both choice and response-time data. Our results show that response-time data is critical at distinguishing among these models and that using choice data alone can lead to inconclusive results for some datasets. In conclusion, we encourage future research to include response-time data in the evaluation of these models.

How similarity between choice options affects decisions from experience: The accentuation-of-differences model.

Traditional theories of decision making require that humans evaluate choice options independently of each other. The independence principle underlying this notion states that the relative choice probability of two options should be independent of the choice set. Previous research demonstrated systematic violations of this principle in decisions from description (context effects), leading to the development of various models explaining them. Yet, the cognitive processes underlying multi-alternative decisions from experience remain unclear. Furthermore, it is not known whether context effects also occur in such decisions, and existing learning models do not predict them. In three experiments, the similarity effect, compromise effect, and attraction effect were explored in a 3-armed bandit task with full feedback. Participants' behavior systematically violated the independence principle, although mostly not in line with past context-effect patterns in decisions from description. The observed similarity effect and the reversals of the compromise and the attraction effects can be explained by a similarity mechanism, according to which options with similar outcomes appear less attractive. We propose the accentuation-of-differences model that relies on this mechanism. We further validated the model in a fourth experiment in which we demonstrated a new violation of independence, the accentuation effect. Across all experiments, the model outperformed traditional reinforcement-learning models in describing the observed findings. Finally, the model's generalizability was confirmed using the Iowa gambling task. In summary, the present work is the first to demonstrate systematic violations of the independence principle in various decisions-from-experience designs and to offer a model to explain the observed phenomena. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Value-based attentional capture affects multi-alternative decision making.

Humans and other animals often violate economic principles when choosing between multiple alternatives, but the underlying neurocognitive mechanisms remain elusive. A robust finding is that adding a third option can alter the relative preference for the original alternatives, but studies disagree on whether the third option's value decreases or increases accuracy. To shed light on this controversy, we used and extended the paradigm of one study reporting a positive effect. However, our four experiments with 147 human participants and a reanalysis of the original data revealed that the positive effect is neither replicable nor reproducible. In contrast, our behavioral and eye-tracking results are best explained by assuming that the third option's value captures attention and thereby impedes accuracy. We propose a computational model that accounts for the complex interplay of value, attention, and choice. Our theory explains how choice sets and environments influence the neurocognitive processes of multi-alternative decision making.