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Organisms and ecological groups accumulate evidence to make decisions. Classic experiments and theoretical studies have explored this process when the correct choice is fixed during each trial. However, we live in a constantly changing…

Neurons and Cognition · Quantitative Biology 2015-10-01 Alan Veliz-Cuba , Zachary P. Kilpatrick , Kresimir Josic

In a constantly changing world, animals must account for environmental volatility when making decisions. To appropriately discount older, irrelevant information, they need to learn the rate at which the environment changes. We develop an…

Neurons and Cognition · Quantitative Biology 2017-01-12 Adrian E Radillo , Alan Veliz-Cuba , Kresimir Josic , Zachary P Kilpatrick

Bias in perceptual decisions comes to pass when the advance knowledge colludes with the current sensory evidence in support of the final choice. The literature on decision making suggests two main hypotheses to account for this kind of…

Neurons and Cognition · Quantitative Biology 2017-10-17 Farzaneh Olianezhad , Maryam Tohidi-Moghaddam , Sajjad Zabbah , Reza Ebrahimpour

We model the joint distribution of choice probabilities and decision times in binary choice tasks as the solution to a problem of optimal sequential sampling, where the agent is uncertain of the utility of each action and pays a constant…

Neurons and Cognition · Quantitative Biology 2015-05-14 Drew Fudenberg , Philipp Strack , Tomasz Strzalecki

For biological experiments aiming at calibrating models with unknown parameters, a good experimental design is crucial, especially for those subject to various constraints, such as financial limitations, time consumption and physical…

Applications · Statistics 2014-07-22 Xiao Lin , Gabriel Terejanu

A canonical foraging task is the patch-leaving problem, in which a forager must decide to leave a current resource in search for another. Theoretical work has derived optimal strategies for when to leave a patch, and experiments have tested…

Neurons and Cognition · Quantitative Biology 2019-12-03 Jacob D. Davidson , Ahmed El Hady

Normative models are often used to describe how humans and animals make decisions. These models treat deliberation as the accumulation of uncertain evidence that terminates with a commitment to a choice. When extended to social groups, such…

Physics and Society · Physics 2023-04-04 Megan Stickler , William Ott , Zachary P. Kilpatrick , Krešimir Josić , Bhargav R. Karamched

Most decisions require information gathering from a stimulus presented with different gaps. Indeed, the brain process of this integration is rarely ambiguous. Recently, it has been claimed that humans can optimally integrate the information…

Neurons and Cognition · Quantitative Biology 2018-10-29 Maryam Tohidi-Moghaddam , Sajjad Zabbah , Farzaneh Olianezhad , Reza Ebrahimpour

What is intuitive: pro-social or anti-social behaviour? To answer this fundamental question, recent studies analyse decision times in game theory experiments under the assumption that intuitive decisions are fast and that deliberation is…

Physics and Society · Physics 2020-04-14 Riccardo Gallotti , Jelena Grujic

Humans and other organisms make decisions choosing between different options, with the aim to maximize the reward and minimize the cost. The main theoretical framework for modeling the decision-making process has been based on the highly…

Neurons and Cognition · Quantitative Biology 2024-11-19 Olga Tapinova , Tal Finkelman , Tamar Reitich-Stolero , Rony Paz , Assaf Tal , Nir S. Gov

In this work, we consider a binary hypothesis testing problem involving a group of human decision-makers. Due to the nature of human behavior, each human decision-maker observes the phenomenon of interest sequentially up to a random length…

Signal Processing · Electrical Eng. & Systems 2023-01-26 Nandan Sriranga , Baocheng Geng , Pramod K. Varshney

To make decisions we are guided by the evidence we collect, as well as the opinions of friends and neighbors. How do we integrate our private beliefs with information we obtain from our social network? To understand the strategies humans…

Physics and Society · Physics 2020-03-04 Bhargav Karamched , Simon Stolarczyk , Zachary Kilpatrick , Krešimir Josić

Although evidence integration to the boundary model has successfully explained a wide range of behavioral and neural data in decision making under uncertainty, how animals learn and optimize the boundary remains unresolved. Here, we propose…

Neural and Evolutionary Computing · Computer Science 2024-08-13 Jamal Esmaily , Rani Moran , Yasser Roudi , Bahador Bahrami

We consider the problem of sequential evaluation, in which an evaluator observes candidates in a sequence and assigns scores to these candidates in an online, irrevocable fashion. Motivated by the psychology literature that has studied…

Machine Learning · Statistics 2023-11-20 Jingyan Wang , Ashwin Pananjady

The drift diffusion model (DDM) is a model of sequential sampling with diffusion (Brownian) signals, where the decision maker accumulates evidence until the process hits a stopping boundary, and then stops and chooses the alternative that…

Econometrics · Economics 2022-10-12 Drew Fudenberg , Whitney K. Newey , Philipp Strack , Tomasz Strzalecki

Animals learn the timing between consecutive events very easily. Their precision is usually proportional to the interval to time (Weber's law for timing). Most current timing models either require a central clock and unbounded accumulator…

Neurons and Cognition · Quantitative Biology 2011-03-15 Francois Rivest , Yoshua Bengio

How choices are made within noisy environments is a central question in the neuroscience of decision making. Previous work has characterized temporal accumulation of evidence for decision-making in static environments. However, real-world…

Neurons and Cognition · Quantitative Biology 2017-10-18 Alex Piet , Ahmed El Hady , Carlos D Brody

Future sequence represents the outcome after executing the action into the environment (i.e. the trajectory onwards). When driven by the information-theoretic concept of mutual information, it seeks maximally informative consequences.…

Machine Learning · Computer Science 2023-11-15 Jianfei Ma

This paper provides a statistical method to test whether a system that performs a binary sequential hypothesis test is optimal in the sense of minimizing the average decision times while taking decisions with given reliabilities. The…

Information Theory · Computer Science 2018-01-08 Meik Dörpinghaus , Izaak Neri , Édgar Roldán , Heinrich Meyr , Frank Jülicher

We consider a decision maker who must choose an action in order to maximize a reward function that depends also on an unknown parameter {\Theta}. The decision maker can delay taking the action in order to experiment and gather additional…

Machine Learning · Statistics 2021-06-22 Victor F. Araman , Rene Caldentey
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