Lie-Algebraic Approach for the Leaky Competing Accumulator Model of Decision Making

2017 ◽  
Author(s):  
Chi-Fai Lo
Keyword(s):  
Decision Making ◽  
Algebraic Approach ◽  
Accumulator Model

An algebraic approach to N-soft sets with application in decision-making using TOPSIS

2021 ◽  
pp. 1-21
Author(s):  
Muhammad Shabir ◽  
Rimsha Mushtaq ◽  
Munazza Naz
Keyword(s):  
Decision Making ◽  
Mathematical Models ◽  
Real World ◽  
Algebraic Approach ◽  
Multi Criteria Decision Making ◽  
Commutative Monoids ◽  
Soft Sets ◽  
Algebraic Properties ◽  
Different Types ◽  
Selection Of

In this paper, we focus on two main objectives. Firstly, we define some binary and unary operations on N-soft sets and study their algebraic properties. In unary operations, three different types of complements are studied. We prove De Morgan’s laws concerning top complements and for bottom complements for N-soft sets where N is fixed and provide a counterexample to show that De Morgan’s laws do not hold if we take different N. Then, we study different collections of N-soft sets which become idempotent commutative monoids and consequently show, that, these monoids give rise to hemirings of N-soft sets. Some of these hemirings are turned out as lattices. Finally, we show that the collection of all N-soft sets with full parameter set E and collection of all N-soft sets with parameter subset A are Stone Algebras. The second objective is to integrate the well-known technique of TOPSIS and N-soft set-based mathematical models from the real world. We discuss a hybrid model of multi-criteria decision-making combining the TOPSIS and N-soft sets and present an algorithm with implementation on the selection of the best model of laptop.

A biophysical neural accumulator model of decision making in an antisaccade task

2007 ◽  
Vol 70 (7-9) ◽  
pp. 1390-1402 ◽  
Author(s):  
Vassilis Cutsuridis ◽  
Ioannis Kahramanoglou ◽  
Nikolaos Smyrnis ◽  
Ioannis Evdokimidis ◽  
Stavros Perantonis
Keyword(s):  
Decision Making ◽  
Antisaccade Task ◽  
Accumulator Model

scholarly journals The dual accumulator model of strategic deliberation and decision making.

2020 ◽  
Vol 127 (4) ◽  
pp. 477-504 ◽  
Author(s):  
Russell Golman ◽  
Sudeep Bhatia ◽  
Patrick Bodilly Kane
Keyword(s):  
Decision Making ◽  
Accumulator Model

scholarly journals Neurally constrained modeling of speed-accuracy tradeoff during visual search: gated accumulation of modulated evidence

2019 ◽  
Vol 121 (4) ◽  
pp. 1300-1314 ◽  
Author(s):  
Mathieu Servant ◽  
Gabriel Tillman ◽  
Jeffrey D. Schall ◽  
Gordon D. Logan ◽  
Thomas J. Palmeri
Keyword(s):  
Decision Making ◽  
Visual Search ◽  
Response Times ◽  
Frontal Eye Field ◽  
Search Performance ◽  
Model Framework ◽  
Accumulator Model ◽  
Eye Field ◽  
Speed Accuracy ◽  
Accuracy Tradeoff

Stochastic accumulator models account for response times and errors in perceptual decision making by assuming a noisy accumulation of perceptual evidence to a threshold. Previously, we explained saccade visual search decision making by macaque monkeys with a stochastic multiaccumulator model in which accumulation was driven by a gated feed-forward integration to threshold of spike trains from visually responsive neurons in frontal eye field that signal stimulus salience. This neurally constrained model quantitatively accounted for response times and errors in visual search for a target among varying numbers of distractors and replicated the dynamics of presaccadic movement neurons hypothesized to instantiate evidence accumulation. This modeling framework suggested strategic control over gate or over threshold as two potential mechanisms to accomplish speed-accuracy tradeoff (SAT). Here, we show that our gated accumulator model framework can account for visual search performance under SAT instructions observed in a milestone neurophysiological study of frontal eye field. This framework captured key elements of saccade search performance, through observed modulations of neural input, as well as flexible combinations of gate and threshold parameters necessary to explain differences in SAT strategy across monkeys. However, the trajectories of the model accumulators deviated from the dynamics of most presaccadic movement neurons. These findings demonstrate that traditional theoretical accounts of SAT are incomplete descriptions of the underlying neural adjustments that accomplish SAT, offer a novel mechanistic account of decision-making mechanisms during speed-accuracy tradeoff, and highlight questions regarding the identity of model and neural accumulators. NEW & NOTEWORTHY A gated accumulator model is used to elucidate neurocomputational mechanisms of speed-accuracy tradeoff. Whereas canonical stochastic accumulators adjust strategy only through variation of an accumulation threshold, we demonstrate that strategic adjustments are accomplished by flexible combinations of both modulation of the evidence representation and adaptation of accumulator gate and threshold. The results indicate how model-based cognitive neuroscience can translate between abstract cognitive models of performance and neural mechanisms of speed-accuracy tradeoff.

Analytical Calculation of Errors in Time and Value Perception Due to a Subjective Time Accumulator: A Mechanistic Model and the Generation of Weber’s Law

2016 ◽  
Vol 28 (1) ◽  
pp. 89-117 ◽  
Author(s):  
Vijay Mohan K. Namboodiri ◽  
Stefan Mihalas ◽  
Marshall G. Hussain Shuler
Keyword(s):  
Decision Making ◽  
Time Perception ◽  
Experimental Testing ◽  
Mechanistic Model ◽  
Analytical Calculation ◽  
Temporal Discounting ◽  
Subjective Time ◽  
Weber’S Law ◽  
Weber's Law ◽  
Accumulator Model

It has been previously shown (Namboodiri, Mihalas, Marton, & Hussain Shuler, 2014 ) that an evolutionary theory of decision making and time perception is capable of explaining numerous behavioral observations regarding how humans and animals decide between differently delayed rewards of differing magnitudes and how they perceive time. An implementation of this theory using a stochastic drift-diffusion accumulator model (Namboodiri, Mihalas, & Hussain Shuler, 2014a ) showed that errors in time perception and decision making approximately obey Weber’s law for a range of parameters. However, prior calculations did not have a clear mechanistic underpinning. Further, these calculations were only approximate, with the range of parameters being limited. In this letter, we provide a full analytical treatment of such an accumulator model, along with a mechanistic implementation, to calculate the expression of these errors for the entirety of the parameter space. In our mechanistic model, Weber’s law results from synaptic facilitation and depression within the feedback synapses of the accumulator. Our theory also makes the prediction that the steepness of temporal discounting can be affected by requiring the precise timing of temporal intervals. Thus, by presenting exact quantitative calculations, this work provides falsifiable predictions for future experimental testing.

Neurally constrained multiple-accumulator model of perceptual decision making

2010 ◽  
Author(s):  
Thomas J. Palmeri ◽  
Braden A. Purcell ◽  
Richard P. Heitz ◽  
Jeffrey D. Schall ◽  
Gordon D. Logan
Keyword(s):  
Decision Making ◽  
Perceptual Decision Making ◽  
Perceptual Decision ◽  
Accumulator Model

scholarly journals A New Algebraic Approach to Decision Making in a Railway Interlocking System Based on Preprocess

2018 ◽  
Vol 2018 ◽  
pp. 1-14 ◽  
Author(s):  
Antonio Hernando ◽  
Roberto Maestre ◽  
Eugenio Roanes-Lozano
Keyword(s):  
Decision Making ◽  
Computer Algebra ◽  
Road Traffic ◽  
Algebraic Approach ◽  
Algebraic Model ◽  
Medium Size ◽  
Scheduling Problems ◽  
Traffic Light ◽  
Railway Network ◽  
Railway Networks

The safety of railway networks is a very important issue. Roughly speaking, it can be split into safety along lines and safety of railway facilities such as stations, junctions, yards, etc. In modern networks the safety along lines is controlled by automatic block systems that do not give clearance to trains to enter a section (block) until the latter is detected to be unoccupied. Meanwhile, the safety within railway facilities is supervised by railway interlocking systems. Decision making in a railway interlocking is a very important issue which is considered to be very labour-intensive. Decision-making in both automatic block systems and railway interlocking systems, unlike road traffic light systems, is not based on time (they are not scheduling problems) but in space. Basically, two different trains should never be allowed to access the same section (whatever time has passed). There are many different approaches to automate decision-making in railway interlocking systems. The classic approaches are offline: only certain routes are allowed and their compatibility is decided in advance. Meanwhile, modern approaches make decisions in real time and are independent from the topology of the railway network, but can be applied only to small or medium size railway networks. Nevertheless, these last approaches have the following drawbacks: the performances are very dependent on the number of trains in the railway network; and are unsuitable to large networks since they take long time to be run. On the other hand, algebraic approaches based on computer algebra concepts have been used in artificial intelligence for implementing expert systems. In this paper we present a completely new algebraic model, based on these concepts of computer algebra that overcomes these drawbacks: the performance of our approach is independent of the number of trains in the railway network and also is suitable for large railway networks.

scholarly journals Coherent combination of probabilistic outputs for group decision making: an algebraic approach

OR Spectrum ◽  
2020 ◽  
Vol 42 (2) ◽  
pp. 499-528
Author(s):  
Manuele Leonelli ◽  
Eva Riccomagno ◽  
Jim Q. Smith
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Algebraic Approach
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