Varun Dutt - Academia.edu (original) (raw)

Papers by Varun Dutt

We developed a system dynamics model for a simple, but important stock and flows task where the o... more We developed a system dynamics model for a simple, but important stock and flows task where the objective was to control the water level in a tank within an acceptable range of the goal, over a number of time periods, in the presence of an unknown environmental inflow and outflow. We also report how this model accounts for human behavior, using behavioral data we collected from human subjects in the task. This exercise helped us understand the strategy and mechanisms our participants used in the simple stock and flows task and develop a model on the task. The model provides an integrated explanation on how the variation in the parameters of the model affects the performance and learning for the participant's task. Finally, we present the model's validity and predictions derived by looking into how the human data fits different learning conditions.

Decisions from description and experience impact the psychology of policymaking on climate change... more Decisions from description and experience impact the psychology of policymaking on climate change. Yet, experiencing climate change consequences in movies and reading descriptive messages about the consequences in newspapers and reports seem to have fallen on deaf ears. This study investigates how a description or experience of cost, timing, and probability of future climate consequences affects people's risky behavior for climate change. In a laboratory experiment, carbon-tax consequences were presented to participants in one of two forms: a written description, where the cost, timing, and probability were explicitly provided; or experience, where the cost, timing, and probability were sampled through unlabeled buttons. Eight problems, each with a safe option and a risky option, were presented in description and experience such that the probability of consequences on the risky option was low or high, the timing was early or late, and the cost was small or large. Results indicat...

Past research has shown that a majority of people exhibit robust linear thinking for nonlinear ch... more Past research has shown that a majority of people exhibit robust linear thinking for nonlinear changes in their decision environment. We argue that linear thinking could be particularly problematic in the case of interpreting carbon-dioxide's (CO₂) lifetime in the earth's atmosphere. Participants from policy and non-policy backgrounds were asked to rank five ranges of CO₂ percentages to be removed from the atmosphere according to their impact on CO₂'s lifetime in two separate conditions: Aid and no-Aid. In the Aid condition, participants were provided with a descriptive decision aid through instructions that might enable them to answer the problem correct, while this aid was absent in the no-Aid condition. Two problems were presented to each participant in random order: Linear, where a ranking based upon linear thinking yielded a correct rank order; and Nonlinear, where a ranking based upon linear think...

Hills and Hertwig (2012) challenge the proposed similarity of the exploration-exploitation transi... more Hills and Hertwig (2012) challenge the proposed similarity of the exploration-exploitation transitions found in Gonzalez and Dutt (2011) between the two experimental paradigms of decisions from experience (sampling and repeated-choice), which was predicted by an Instance-Based Learning (IBL) model. The heart of their argument is that in the sampling paradigm, an impression of reduced exploration over time (alternation rate, A-rate) is produced by an inverse relationship between the sample size and the A-rate, and the aggregation of participants with different sample sizes. They suggest a normalization of the A-rate, which produces constant A-rate curves during sampling, and conclude with certain "ensuing problems for the IBL model." We show that: the reduction of A-rate during sampling occurs even when sample length is controlled for; that regardless of the sampling length, the maximization behavior during sampling predicts the final choice; and that the IBL model accounts...

A 2007 U.N. survey found that 54% of Americans advocate ―wait-and-see‖ behavior on policies that ... more A 2007 U.N. survey found that 54% of Americans advocate ―wait-and-see‖ behavior on policies that mitigate climate change, i.e., they infer that climate mitigation actions can be deferred until there are clear signs of danger. By evaluating different cognitive factors that influence human behavior, this thesis builds a framework that provides answers to an important question: why do people advocate wait-and-see behavior on climate change? One cognitive factor is misperceptions of feedback (i.e., ignorance of large feedback delays between CO2 emission decisions and the corresponding changes in CO2 concentration). Results reveal that the use of simulation tools, that provide repeated feedback about decision actions and corresponding consequences, is likely to enable people to overcome these misperceptions. A second factor is people's reliance on correlational or linear thinking (that the shape of CO2 emissions and CO2 concentration should look alike). Results reveal that the use of...

Artificial Intelligence and Cognitive Modeling (modeling human behavior in dynamic tasks trough c... more Artificial Intelligence and Cognitive Modeling (modeling human behavior in dynamic tasks trough computer algorithms) Human-Computer Interaction (Study of the interaction between people and computers) Situation Awareness (recognition, comprehension, and projection of a situation in the decision environment) Judgment and Decision Making (understanding human behavior in problems involving risk and uncertainty) Environmental Decision Making (understanding human behavior in environmental problems)

Journal of Dynamic Decision Making, 2016

Before making a choice we often search and explore the options available. For example, we try clo... more Before making a choice we often search and explore the options available. For example, we try clothes on before selecting the one to buy and we search for career options before deciding a career to pursue. Although the exploration process, where one is free to sample available options is pervasive, we know little about how and why humans explore an environment before making choices. This research contributes to the clarification of some of the phenomena that describe how people perform search during free sampling: we find a gradual decrease of exploration and, in parallel, a tendency to explore and choose options of high value. These patterns provide support to the existence of learning and an exploration-exploitation tradeoffs that may occur during free sampling. Thus, exploration in free sampling is not led by the purely epistemic value of the available options. Rather, exploration during free sampling is a learning process that is influenced by memory effects and by the value of the o...

Human Factors: The Journal of the Human Factors and Ergonomics Society, 2020

Objective We aim to learn about the cognitive mechanisms governing the decisions of attackers and... more Objective We aim to learn about the cognitive mechanisms governing the decisions of attackers and defenders in cybersecurity involving intrusion detection systems (IDSs). Background Prior research has experimentally studied the role of the presence and accuracy of IDS alerts on attacker’s and defender’s decisions using a game-theoretic approach. However, little is known about the cognitive mechanisms that govern these decisions. Method To investigate the cognitive mechanisms governing the attacker’s and defender’s decisions in the presence of IDSs of different accuracies, instance-based learning (IBL) models were developed. One model (NIDS) disregarded the IDS alerts and one model (IDS) considered them in the instance structure. Both the IDS and NIDS models were trained in an existing dataset where IDSs were either absent or present and they possessed different accuracies. The calibrated IDS model was tested in a newly collected test dataset where IDSs were present 50% of the time a...

International Journal on Cyber Situational Awareness, 2019

Current research in cyber-security is not focused on human decision-making. The primary objective... more Current research in cyber-security is not focused on human decision-making. The primary objective of this study is to address this gap and investigate how cognitive processes proposed by Instance-based Learning Theory (IBLT) like reliance on recency and frequency, attention to opponent's actions, and cognitive noise are influenced by the effectiveness of vulnerability patching. Data involving participants performing as hackers and analysts was collected in a lab-based experiment in two patching conditions: effective (N = 50) and less-effective (N = 50). In effective (less-effective) patching, computer systems were in a non-vulnerable state (i.e., immune to cyber-attacks) 90% (50%) of the time after patching. An IBL model accounted for human decisions and revealed low (high) reliance on recency and frequency, attention to opponent's actions, and cognitive noise for hacker (analyst) in effective patching. Whereas, it revealed opposite results for less-effective patching. We highlight the implications of our findings for cyber decisionmaking.

International Journal on Cyber Situational Awareness, 2018

Intrusion Detection Systems (IDSs) help in creating cyber situational awareness for defenders by ... more Intrusion Detection Systems (IDSs) help in creating cyber situational awareness for defenders by providing recommendations. Prior research in simulation and game-theory has revealed that the presence and accuracy of IDS-like recommendations influence the decisions of defenders and adversaries. In the current paper, we present novel analyses of prior research by analyzing the sequential decisions of defenders and adversaries over repeated trials. Specifically, we developed computational cognitive models based upon Instance-Based Learning Theory (IBLT) to capture the dynamics of the sequential decisions made by defenders and adversaries across numerous conditions that differed in the IDS's availability and accuracy. We found that cognitive mechanisms based upon recency, frequency, and variability helped account for adversarial and defender decisions better than the optimal Nash solutions. We discuss the implications of our results for adversarial-and-defender decisions in the cyber-world.

Frontiers in psychology, 2018

Research shows that people's wait-and-see preferences for actions against climate change are ... more Research shows that people's wait-and-see preferences for actions against climate change are a result of several factors, including cognitive misconceptions. The use of simulation tools could help reduce these misconceptions concerning Earth's climate. However, it is still unclear whether the learning in these tools is of the problem's surface features (dimensions of emissions and absorptions and cover-story used) or of the problem's structural features (how emissions and absorptions cause a change in CO concentration under different CO concentration scenarios). Also, little is known on how problem's difficulty in these tools (the shape of CO concentration trajectory), as well as the use of these tools as a decision aid influences performance. The primary objective of this paper was to investigate how learning about Earth's climate via simulation tools is influenced by problem's surface and structural features, problem's difficulty, and decision aids....

Frontiers in psychology, 2018

Research shows that people tend to overweight small probabilities in description and underweight ... more Research shows that people tend to overweight small probabilities in description and underweight them in experience, thereby leading to a different pattern of choices between description and experience; a phenomenon known as the Description-Experience (DE) gap. However, little is known on how the addition of an intermediate option and contextual framing influences the DE gap and people's search strategies. This paper tests the effects of an intermediate option and contextual framing on the DE gap and people's search strategies, where problems require search for information before a consequential choice. In the first experiment, 120 participants made choice decisions across investment problems that differed in the absence or presence of an intermediate option. Results showed that adding an intermediate option did not reduce the DE gap on the maximizing option across a majority of problems. There were a large majority of choices for the intermediate option. Furthermore, there ...

Journal of Behavioral Decision Making, 2013

The search for different options before making a consequential choice is a central aspect of many... more The search for different options before making a consequential choice is a central aspect of many important decisions, such as mate selection or purchasing a house. Despite its importance, surprisingly little is known about how search and choice are affected by the observed and objective properties of the decision problem. Here, we analyze the effects of two key properties in a binary choice task: the options' observed and objective values, and the variability of payoffs. First, in a large public data set of a binary choice task, we investigate how the observed value and variability relate to decision-makers' efforts and preferences during search. Furthermore, we test how these properties influence the chance of correctly identifying the objectively maximizing option, and how they affect choice. Second, we designed a novel experiment to systematically analyze the role of the objective difference between the options. We find that a larger objective difference between options increases the chance for correctly identifying the maximizing option, but it does not affect behavior during search and choice.

Lecture Notes in Computer Science, 2011

In a corporate network, the situation awareness (SA) of a security analyst is of particular inter... more In a corporate network, the situation awareness (SA) of a security analyst is of particular interest. A security analyst is in charge of observing the online operations of a corporate network (e.g., an online retail company with an external webserver and an internal fileserver) from threats of random or organized cyber-attacks. The current work describes a cognitive Instance-based Learning (IBL) model of the recognition and comprehension processes of a security analyst in a simple cyber-attack scenario. The IBL model first recognizes cyber-events (e.g., execution of a file on a server) in the network based upon events' situation attributes and the similarity of events' attributes to past experiences (instances) stored in analyst's memory. Then, the model reasons about a sequence of observed events being a cyber-attack or not, based upon instances retrieved from memory and the risk-tolerance of a simulated analyst. The execution of the IBL model generates predictions of the recognition and comprehension processes of security analyst in a cyber-attack. An analyst's decisions are evaluated in the model based upon two cyber SA metrics of accuracy and timeliness of analyst's decision actions. Future work in this area will focus on collecting human data to validate the predictions made by the model.

Principles, Methods and Applications

In a corporate network, the situation awareness (SA) of a security analyst is of particular inter... more In a corporate network, the situation awareness (SA) of a security analyst is of particular interest. The current work describes a cognitive Instance-Based Learning (IBL) model of an analyst’s recognition and comprehension processes in a cyber-attack scenario. The IBL model first recognizes network events based upon events’ situation attributes and their similarity to past experiences (instances) stored in the model’s memory. Then, the model comprehends a sequence of observed events as being a cyber-attack or not, based upon instances retrieved from its memory, similarity mechanism used, and the model’s risk-tolerance. The execution of the model generates predictions about the recognition and comprehension processes of an analyst in a cyber-attack. A security analyst’s decisions in the model are evaluated based upon two cyber-SA metrics of accuracy and timeliness. The chapter highlights the potential of this research for design of training and decision support tools for security ana...

Behavior in conflict situations can be influenced by the social information that individuals have... more Behavior in conflict situations can be influenced by the social information that individuals have about their opponents. This paper tests whether an existent Instance-based Learning (IBL) model, built using the Instance-based Learning Theory (IBLT) to explain behavior in a single-person binary-choice task (BCT), can predict behavior in a two-player iterated prisoner's dilemma (IPD) game. The same IBL model is generalized to two conditions in the IPD: Social, where individuals have information about their opponents and their choices; and Non-social, where individuals and opponents lack this information. We expect the single-person IBL model to predict behavior in the Non-social condition better than in the Social condition. However, due to the structural differences between BCT and IPD, we also expect only moderately good model predictions in the Non-social condition. Our results confirm these expectations. These findings highlight the need for additional cognitive mechanisms to account for social information in conflict situations.

PsycEXTRA Dataset

This paper presents an interactive simulation of the effects of emissions and absorptions of anth... more This paper presents an interactive simulation of the effects of emissions and absorptions of anthropogenic carbon dioxide (CO 2) in the atmosphere. The interactive simulation based on the "bathtub" metaphor, was built using the Dynamic Integrated Climate Economy model (DICE)-1992. The interactive tool allows participants to make decisions on the anthropogenic CO 2 emissions, observe the consequences of the decisions and try new decisions. In a laboratory experiment, we tested the participants' ability to control the CO 2 concentration to a realistic amount in the atmosphere over a period of 100 to 200 years. Participants worked on one of two extreme conditions: one rapid, where transfer rate of carbon dioxide was 1.6% per year with CO 2 emission decisions made every 2 years, and other slow, where transfer rate of carbon dioxide was 1.2% per year with CO 2 emission decisions made every 4 years. Due to human incapacity to handle feedback delays and their use of faulty heuristics, we expected participants to find the slow condition harder to control as compared to the rapid condition. Results show that participants had more difficulty achieving control of CO 2 concentration to goal in face of slower dynamics than rapid dynamics. Implications and future of our research findings are discussed.

PsycEXTRA Dataset

• With the mixed tasks, the SRC effect is eliminated. • When spatially compatible and incompatibl... more • With the mixed tasks, the SRC effect is eliminated. • When spatially compatible and incompatible (SRC) trials are mixed, the benefit for the compatible mapping (i.e., the SRC effect) is eliminated (Vu &

Encyclopedia of Information Science and Technology, Third Edition

Sustainability, 2013

Ecological (eco) taxes are promising mechanisms to enable eco-friendly decisions, but few people ... more Ecological (eco) taxes are promising mechanisms to enable eco-friendly decisions, but few people prefer them. In this study, we present a way in which eco-tax options may be communicated to general public to encourage their payment. Our implementation (called "information presentation") takes advantage of the non-linear relationship between eco-tax payments and CO 2 emissions and the human reliance on the proportional-thinking heuristic. According to the proportional-thinking heuristic, people are likely to prefer a small eco-tax increase and judge larger eco-tax increases to cause proportionally greater CO 2 emissions reductions. In an online study, participants were asked to choose between eco-tax increases in two problems: In one, a smaller eco-tax increase resulted in greater CO 2 emissions reduction, while in the other, a smaller tax increase resulted in lesser CO 2 emissions reduction. Although the larger eco-tax increase did not reduce CO 2 emissions the most, across both problems, people judged larger eco-tax increases to cause proportionally greater reductions in CO 2 emissions and preferred smaller tax increases. Thus, eco-tax policies would benefit by presenting information in terms of eco-tax increases, such that smaller eco-tax increases (which are more attractive and are likely to be chosen by people) cause greater CO 2 emissions reductions.

We developed a system dynamics model for a simple, but important stock and flows task where the o... more We developed a system dynamics model for a simple, but important stock and flows task where the objective was to control the water level in a tank within an acceptable range of the goal, over a number of time periods, in the presence of an unknown environmental inflow and outflow. We also report how this model accounts for human behavior, using behavioral data we collected from human subjects in the task. This exercise helped us understand the strategy and mechanisms our participants used in the simple stock and flows task and develop a model on the task. The model provides an integrated explanation on how the variation in the parameters of the model affects the performance and learning for the participant's task. Finally, we present the model's validity and predictions derived by looking into how the human data fits different learning conditions.

Decisions from description and experience impact the psychology of policymaking on climate change... more Decisions from description and experience impact the psychology of policymaking on climate change. Yet, experiencing climate change consequences in movies and reading descriptive messages about the consequences in newspapers and reports seem to have fallen on deaf ears. This study investigates how a description or experience of cost, timing, and probability of future climate consequences affects people's risky behavior for climate change. In a laboratory experiment, carbon-tax consequences were presented to participants in one of two forms: a written description, where the cost, timing, and probability were explicitly provided; or experience, where the cost, timing, and probability were sampled through unlabeled buttons. Eight problems, each with a safe option and a risky option, were presented in description and experience such that the probability of consequences on the risky option was low or high, the timing was early or late, and the cost was small or large. Results indicat...

Past research has shown that a majority of people exhibit robust linear thinking for nonlinear ch... more Past research has shown that a majority of people exhibit robust linear thinking for nonlinear changes in their decision environment. We argue that linear thinking could be particularly problematic in the case of interpreting carbon-dioxide's (CO₂) lifetime in the earth's atmosphere. Participants from policy and non-policy backgrounds were asked to rank five ranges of CO₂ percentages to be removed from the atmosphere according to their impact on CO₂'s lifetime in two separate conditions: Aid and no-Aid. In the Aid condition, participants were provided with a descriptive decision aid through instructions that might enable them to answer the problem correct, while this aid was absent in the no-Aid condition. Two problems were presented to each participant in random order: Linear, where a ranking based upon linear thinking yielded a correct rank order; and Nonlinear, where a ranking based upon linear think...

Hills and Hertwig (2012) challenge the proposed similarity of the exploration-exploitation transi... more Hills and Hertwig (2012) challenge the proposed similarity of the exploration-exploitation transitions found in Gonzalez and Dutt (2011) between the two experimental paradigms of decisions from experience (sampling and repeated-choice), which was predicted by an Instance-Based Learning (IBL) model. The heart of their argument is that in the sampling paradigm, an impression of reduced exploration over time (alternation rate, A-rate) is produced by an inverse relationship between the sample size and the A-rate, and the aggregation of participants with different sample sizes. They suggest a normalization of the A-rate, which produces constant A-rate curves during sampling, and conclude with certain "ensuing problems for the IBL model." We show that: the reduction of A-rate during sampling occurs even when sample length is controlled for; that regardless of the sampling length, the maximization behavior during sampling predicts the final choice; and that the IBL model accounts...

A 2007 U.N. survey found that 54% of Americans advocate ―wait-and-see‖ behavior on policies that ... more A 2007 U.N. survey found that 54% of Americans advocate ―wait-and-see‖ behavior on policies that mitigate climate change, i.e., they infer that climate mitigation actions can be deferred until there are clear signs of danger. By evaluating different cognitive factors that influence human behavior, this thesis builds a framework that provides answers to an important question: why do people advocate wait-and-see behavior on climate change? One cognitive factor is misperceptions of feedback (i.e., ignorance of large feedback delays between CO2 emission decisions and the corresponding changes in CO2 concentration). Results reveal that the use of simulation tools, that provide repeated feedback about decision actions and corresponding consequences, is likely to enable people to overcome these misperceptions. A second factor is people's reliance on correlational or linear thinking (that the shape of CO2 emissions and CO2 concentration should look alike). Results reveal that the use of...

Artificial Intelligence and Cognitive Modeling (modeling human behavior in dynamic tasks trough c... more Artificial Intelligence and Cognitive Modeling (modeling human behavior in dynamic tasks trough computer algorithms) Human-Computer Interaction (Study of the interaction between people and computers) Situation Awareness (recognition, comprehension, and projection of a situation in the decision environment) Judgment and Decision Making (understanding human behavior in problems involving risk and uncertainty) Environmental Decision Making (understanding human behavior in environmental problems)

Journal of Dynamic Decision Making, 2016

Before making a choice we often search and explore the options available. For example, we try clo... more Before making a choice we often search and explore the options available. For example, we try clothes on before selecting the one to buy and we search for career options before deciding a career to pursue. Although the exploration process, where one is free to sample available options is pervasive, we know little about how and why humans explore an environment before making choices. This research contributes to the clarification of some of the phenomena that describe how people perform search during free sampling: we find a gradual decrease of exploration and, in parallel, a tendency to explore and choose options of high value. These patterns provide support to the existence of learning and an exploration-exploitation tradeoffs that may occur during free sampling. Thus, exploration in free sampling is not led by the purely epistemic value of the available options. Rather, exploration during free sampling is a learning process that is influenced by memory effects and by the value of the o...

Human Factors: The Journal of the Human Factors and Ergonomics Society, 2020

Objective We aim to learn about the cognitive mechanisms governing the decisions of attackers and... more Objective We aim to learn about the cognitive mechanisms governing the decisions of attackers and defenders in cybersecurity involving intrusion detection systems (IDSs). Background Prior research has experimentally studied the role of the presence and accuracy of IDS alerts on attacker’s and defender’s decisions using a game-theoretic approach. However, little is known about the cognitive mechanisms that govern these decisions. Method To investigate the cognitive mechanisms governing the attacker’s and defender’s decisions in the presence of IDSs of different accuracies, instance-based learning (IBL) models were developed. One model (NIDS) disregarded the IDS alerts and one model (IDS) considered them in the instance structure. Both the IDS and NIDS models were trained in an existing dataset where IDSs were either absent or present and they possessed different accuracies. The calibrated IDS model was tested in a newly collected test dataset where IDSs were present 50% of the time a...

International Journal on Cyber Situational Awareness, 2019

Current research in cyber-security is not focused on human decision-making. The primary objective... more Current research in cyber-security is not focused on human decision-making. The primary objective of this study is to address this gap and investigate how cognitive processes proposed by Instance-based Learning Theory (IBLT) like reliance on recency and frequency, attention to opponent's actions, and cognitive noise are influenced by the effectiveness of vulnerability patching. Data involving participants performing as hackers and analysts was collected in a lab-based experiment in two patching conditions: effective (N = 50) and less-effective (N = 50). In effective (less-effective) patching, computer systems were in a non-vulnerable state (i.e., immune to cyber-attacks) 90% (50%) of the time after patching. An IBL model accounted for human decisions and revealed low (high) reliance on recency and frequency, attention to opponent's actions, and cognitive noise for hacker (analyst) in effective patching. Whereas, it revealed opposite results for less-effective patching. We highlight the implications of our findings for cyber decisionmaking.

International Journal on Cyber Situational Awareness, 2018

Intrusion Detection Systems (IDSs) help in creating cyber situational awareness for defenders by ... more Intrusion Detection Systems (IDSs) help in creating cyber situational awareness for defenders by providing recommendations. Prior research in simulation and game-theory has revealed that the presence and accuracy of IDS-like recommendations influence the decisions of defenders and adversaries. In the current paper, we present novel analyses of prior research by analyzing the sequential decisions of defenders and adversaries over repeated trials. Specifically, we developed computational cognitive models based upon Instance-Based Learning Theory (IBLT) to capture the dynamics of the sequential decisions made by defenders and adversaries across numerous conditions that differed in the IDS's availability and accuracy. We found that cognitive mechanisms based upon recency, frequency, and variability helped account for adversarial and defender decisions better than the optimal Nash solutions. We discuss the implications of our results for adversarial-and-defender decisions in the cyber-world.

Frontiers in psychology, 2018

Research shows that people's wait-and-see preferences for actions against climate change are ... more Research shows that people's wait-and-see preferences for actions against climate change are a result of several factors, including cognitive misconceptions. The use of simulation tools could help reduce these misconceptions concerning Earth's climate. However, it is still unclear whether the learning in these tools is of the problem's surface features (dimensions of emissions and absorptions and cover-story used) or of the problem's structural features (how emissions and absorptions cause a change in CO concentration under different CO concentration scenarios). Also, little is known on how problem's difficulty in these tools (the shape of CO concentration trajectory), as well as the use of these tools as a decision aid influences performance. The primary objective of this paper was to investigate how learning about Earth's climate via simulation tools is influenced by problem's surface and structural features, problem's difficulty, and decision aids....

Frontiers in psychology, 2018

Research shows that people tend to overweight small probabilities in description and underweight ... more Research shows that people tend to overweight small probabilities in description and underweight them in experience, thereby leading to a different pattern of choices between description and experience; a phenomenon known as the Description-Experience (DE) gap. However, little is known on how the addition of an intermediate option and contextual framing influences the DE gap and people's search strategies. This paper tests the effects of an intermediate option and contextual framing on the DE gap and people's search strategies, where problems require search for information before a consequential choice. In the first experiment, 120 participants made choice decisions across investment problems that differed in the absence or presence of an intermediate option. Results showed that adding an intermediate option did not reduce the DE gap on the maximizing option across a majority of problems. There were a large majority of choices for the intermediate option. Furthermore, there ...

Journal of Behavioral Decision Making, 2013

The search for different options before making a consequential choice is a central aspect of many... more The search for different options before making a consequential choice is a central aspect of many important decisions, such as mate selection or purchasing a house. Despite its importance, surprisingly little is known about how search and choice are affected by the observed and objective properties of the decision problem. Here, we analyze the effects of two key properties in a binary choice task: the options' observed and objective values, and the variability of payoffs. First, in a large public data set of a binary choice task, we investigate how the observed value and variability relate to decision-makers' efforts and preferences during search. Furthermore, we test how these properties influence the chance of correctly identifying the objectively maximizing option, and how they affect choice. Second, we designed a novel experiment to systematically analyze the role of the objective difference between the options. We find that a larger objective difference between options increases the chance for correctly identifying the maximizing option, but it does not affect behavior during search and choice.

Lecture Notes in Computer Science, 2011

In a corporate network, the situation awareness (SA) of a security analyst is of particular inter... more In a corporate network, the situation awareness (SA) of a security analyst is of particular interest. A security analyst is in charge of observing the online operations of a corporate network (e.g., an online retail company with an external webserver and an internal fileserver) from threats of random or organized cyber-attacks. The current work describes a cognitive Instance-based Learning (IBL) model of the recognition and comprehension processes of a security analyst in a simple cyber-attack scenario. The IBL model first recognizes cyber-events (e.g., execution of a file on a server) in the network based upon events' situation attributes and the similarity of events' attributes to past experiences (instances) stored in analyst's memory. Then, the model reasons about a sequence of observed events being a cyber-attack or not, based upon instances retrieved from memory and the risk-tolerance of a simulated analyst. The execution of the IBL model generates predictions of the recognition and comprehension processes of security analyst in a cyber-attack. An analyst's decisions are evaluated in the model based upon two cyber SA metrics of accuracy and timeliness of analyst's decision actions. Future work in this area will focus on collecting human data to validate the predictions made by the model.

Principles, Methods and Applications

In a corporate network, the situation awareness (SA) of a security analyst is of particular inter... more In a corporate network, the situation awareness (SA) of a security analyst is of particular interest. The current work describes a cognitive Instance-Based Learning (IBL) model of an analyst’s recognition and comprehension processes in a cyber-attack scenario. The IBL model first recognizes network events based upon events’ situation attributes and their similarity to past experiences (instances) stored in the model’s memory. Then, the model comprehends a sequence of observed events as being a cyber-attack or not, based upon instances retrieved from its memory, similarity mechanism used, and the model’s risk-tolerance. The execution of the model generates predictions about the recognition and comprehension processes of an analyst in a cyber-attack. A security analyst’s decisions in the model are evaluated based upon two cyber-SA metrics of accuracy and timeliness. The chapter highlights the potential of this research for design of training and decision support tools for security ana...

Behavior in conflict situations can be influenced by the social information that individuals have... more Behavior in conflict situations can be influenced by the social information that individuals have about their opponents. This paper tests whether an existent Instance-based Learning (IBL) model, built using the Instance-based Learning Theory (IBLT) to explain behavior in a single-person binary-choice task (BCT), can predict behavior in a two-player iterated prisoner's dilemma (IPD) game. The same IBL model is generalized to two conditions in the IPD: Social, where individuals have information about their opponents and their choices; and Non-social, where individuals and opponents lack this information. We expect the single-person IBL model to predict behavior in the Non-social condition better than in the Social condition. However, due to the structural differences between BCT and IPD, we also expect only moderately good model predictions in the Non-social condition. Our results confirm these expectations. These findings highlight the need for additional cognitive mechanisms to account for social information in conflict situations.

PsycEXTRA Dataset

This paper presents an interactive simulation of the effects of emissions and absorptions of anth... more This paper presents an interactive simulation of the effects of emissions and absorptions of anthropogenic carbon dioxide (CO 2) in the atmosphere. The interactive simulation based on the "bathtub" metaphor, was built using the Dynamic Integrated Climate Economy model (DICE)-1992. The interactive tool allows participants to make decisions on the anthropogenic CO 2 emissions, observe the consequences of the decisions and try new decisions. In a laboratory experiment, we tested the participants' ability to control the CO 2 concentration to a realistic amount in the atmosphere over a period of 100 to 200 years. Participants worked on one of two extreme conditions: one rapid, where transfer rate of carbon dioxide was 1.6% per year with CO 2 emission decisions made every 2 years, and other slow, where transfer rate of carbon dioxide was 1.2% per year with CO 2 emission decisions made every 4 years. Due to human incapacity to handle feedback delays and their use of faulty heuristics, we expected participants to find the slow condition harder to control as compared to the rapid condition. Results show that participants had more difficulty achieving control of CO 2 concentration to goal in face of slower dynamics than rapid dynamics. Implications and future of our research findings are discussed.

PsycEXTRA Dataset

• With the mixed tasks, the SRC effect is eliminated. • When spatially compatible and incompatibl... more • With the mixed tasks, the SRC effect is eliminated. • When spatially compatible and incompatible (SRC) trials are mixed, the benefit for the compatible mapping (i.e., the SRC effect) is eliminated (Vu &

Encyclopedia of Information Science and Technology, Third Edition

Sustainability, 2013

Ecological (eco) taxes are promising mechanisms to enable eco-friendly decisions, but few people ... more Ecological (eco) taxes are promising mechanisms to enable eco-friendly decisions, but few people prefer them. In this study, we present a way in which eco-tax options may be communicated to general public to encourage their payment. Our implementation (called "information presentation") takes advantage of the non-linear relationship between eco-tax payments and CO 2 emissions and the human reliance on the proportional-thinking heuristic. According to the proportional-thinking heuristic, people are likely to prefer a small eco-tax increase and judge larger eco-tax increases to cause proportionally greater CO 2 emissions reductions. In an online study, participants were asked to choose between eco-tax increases in two problems: In one, a smaller eco-tax increase resulted in greater CO 2 emissions reduction, while in the other, a smaller tax increase resulted in lesser CO 2 emissions reduction. Although the larger eco-tax increase did not reduce CO 2 emissions the most, across both problems, people judged larger eco-tax increases to cause proportionally greater reductions in CO 2 emissions and preferred smaller tax increases. Thus, eco-tax policies would benefit by presenting information in terms of eco-tax increases, such that smaller eco-tax increases (which are more attractive and are likely to be chosen by people) cause greater CO 2 emissions reductions.