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Should I stay or should I go? How the human brain manages the trade-off between exploitation and exploration

In Jon Driver, Patrick Haggard & Tim Shallice (eds.), Mental Processes in the Human Brain. Oxford University Press (2008)

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  1. Exploration and exploitation of Victorian science in Darwin’s reading notebooks.Jaimie Murdock, Colin Allen & Simon DeDeo - 2017 - Cognition 159 (C):117-126.
    Search in an environment with an uncertain distribution of resources involves a trade-off between exploitation of past discoveries and further exploration. This extends to information foraging, where a knowledge-seeker shifts between reading in depth and studying new domains. To study this decision-making process, we examine the reading choices made by one of the most celebrated scientists of the modern era: Charles Darwin. From the full-text of books listed in his chronologically-organized reading journals, we generate topic models to quantify his local (...)
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  • The anatomy of choice: active inference and agency.Karl Friston, Philipp Schwartenbeck, Thomas FitzGerald, Michael Moutoussis, Timothy Behrens & Raymond J. Dolan - 2013 - Frontiers in Human Neuroscience 7.
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  • Observing others stay or switch – How social prediction errors are integrated into reward reversal learning.Niklas Ihssen, Thomas Mussweiler & David E. J. Linden - 2016 - Cognition 153 (C):19-32.
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  • A bilingual disadvantage in metacognitive processing.Tomas Folke, Julia Ouzia, Peter Bright, Benedetto De Martino & Roberto Filippi - 2016 - Cognition 150 (C):119-132.
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  • Connecting cognition and consumer choice.Daniel M. Bartels & Eric J. Johnson - 2015 - Cognition 135:47-51.
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  • Optimality and Some of Its Discontents: Successes and Shortcomings of Existing Models for Binary Decisions.Philip Holmes & Jonathan D. Cohen - 2014 - Topics in Cognitive Science 6 (2):258-278.
    We review how leaky competing accumulators (LCAs) can be used to model decision making in two‐alternative, forced‐choice tasks, and we show how they reduce to drift diffusion (DD) processes in special cases. As continuum limits of the sequential probability ratio test, DD processes are optimal in producing decisions of specified accuracy in the shortest possible time. Furthermore, the DD model can be used to derive a speed–accuracy trade‐off that optimizes reward rate for a restricted class of two alternative forced‐choice decision (...)
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  • An opportunity cost model of subjective effort and task performance.Robert Kurzban, Angela Duckworth, Joseph Kable & Justus Myers - 2013 - Behavioral and Brain Sciences 36 (6):661–79.
    Why does performing certain tasks cause the aversive experience of mental effort and concomitant deterioration in task performance? One explanation posits a physical resource that is depleted over time. We propose an alternative explanation that centers on mental representations of the costs and benefits associated with task performance. Specifically, certain computational mechanisms, especially those associated with executive function, can be deployed for only a limited number of simultaneous tasks at any given moment. Consequently, the deployment of these computational mechanisms carries (...)
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  • Children adapt their questions to achieve efficient search.Azzurra Ruggeri & Tania Lombrozo - 2015 - Cognition 143 (C):203-216.
    One way to learn about the world is by asking questions. We investigate how younger children (7- to 8-year-olds), older children (9- to 11-year-olds), and young adults (17- to 18-year-olds) ask questions to identify the cause of an event. We find a developmental shift in children’s reliance on hypothesis-scanning questions (which test hypotheses directly) versus constraint-seeking questions (which reduce the space of hypotheses), but also that all age groups ask more constraint-seeking questions when hypothesis-scanning questions are least likely to pay (...)
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  • Uncertainty and Exploration in a Restless Bandit Problem.Maarten Speekenbrink & Emmanouil Konstantinidis - 2015 - Topics in Cognitive Science 7 (2):351-367.
    Decision making in noisy and changing environments requires a fine balance between exploiting knowledge about good courses of action and exploring the environment in order to improve upon this knowledge. We present an experiment on a restless bandit task in which participants made repeated choices between options for which the average rewards changed over time. Comparing a number of computational models of participants’ behavior in this task, we find evidence that a substantial number of them balanced exploration and exploitation by (...)
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  • What is in the feedback? Effect of induced happiness vs. sadness on probabilistic learning with vs. without exploration.Jasmina Bakic, Rudi De Raedt, Marieke Jepma & Gilles Pourtois - 2015 - Frontiers in Human Neuroscience 9.
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  • Exploration and Exploitation During Sequential Search.Gregory Dam & Konrad Körding - 2009 - Cognitive Science 33 (3):530-541.
    When we learn how to throw darts we adjust how we throw based on where the darts stick. Much of skill learning is computationally similar in that we learn using feedback obtained after the completion of individual actions. We can formalize such tasks as a search problem; among the set of all possible actions, find the action that leads to the highest reward. In such cases our actions have two objectives: we want to best utilize what we already know (exploitation), (...)
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  • Causes of Individual Differences in Animal Exploration and Search.Simon M. Reader - 2015 - Topics in Cognitive Science 7 (3):451-468.
    Numerous studies have documented individual differences in exploratory tendencies and other phenomena related to search, and these differences have been linked to fitness. Here, I discuss the origins of these differences, focusing on how experience shapes animal search and exploration. The origin of individual differences will also depend upon the alternatives to exploration that are available. Given that search and exploration frequently carry significant costs, we might expect individuals to utilize cues indicating the potential net payoffs of exploration versus the (...)
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  • Altered Statistical Learning and Decision-Making in Methamphetamine Dependence: Evidence from a Two-Armed Bandit Task.Katia M. Harlé, Shunan Zhang, Max Schiff, Scott Mackey, Martin P. Paulus & Angela J. Yu - 2015 - Frontiers in Psychology 6.
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  • Commentary on Mata and von Helversen: Foraging Theory as a Paradigm Shift for Cognitive Aging.Elizabeth A. L. Stine-Morrow - 2015 - Topics in Cognitive Science 7 (3):535-542.
    Mata and von Helversen's integrative review of adult age differences in search performance makes a good case that cognitive control may impact certain aspects of self-regulation of search. However, information foraging as a framework also offers an avenue to consider how adults of different ages adapt to age-related changes in cognition, such as in cognitive control.
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  • Exploration, novelty, surprise, and free energy minimization.Philipp Schwartenbeck, Thomas FitzGerald, Raymond J. Dolan & Karl Friston - 2013 - Frontiers in Psychology 4.
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  • Efficient multitasking: parallel versus serial processing of multiple tasks.Rico Fischer & Franziska Plessow - 2015 - Frontiers in Psychology 6.
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  • Rivals in the dark: How competition influences search in decisions under uncertainty.Nathaniel D. Phillips, Ralph Hertwig, Yaakov Kareev & Judith Avrahami - 2014 - Cognition 133 (1):104-119.
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  • The Nature of Belief-Directed Exploratory Choice in Human Decision-Making.W. Bradley Knox, A. Ross Otto, Peter Stone & Bradley C. Love - 2011 - Frontiers in Psychology 2.
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  • Novelty and Inductive Generalization in Human Reinforcement Learning.Samuel J. Gershman & Yael Niv - 2015 - Topics in Cognitive Science 7 (3):391-415.
    In reinforcement learning, a decision maker searching for the most rewarding option is often faced with the question: What is the value of an option that has never been tried before? One way to frame this question is as an inductive problem: How can I generalize my previous experience with one set of options to a novel option? We show how hierarchical Bayesian inference can be used to solve this problem, and we describe an equivalence between the Bayesian model and (...)
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  • A face for all seasons: Searching for context-specific leadership traits and discovering a general preference for perceived health.Brian R. Spisak, Nancy M. Blaker, Carmen E. Lefevre, Fhionna R. Moore & Kleis F. B. Krebbers - 2014 - Frontiers in Human Neuroscience 8.
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  • Keep focussing: striatal dopamine multiple functions resolved in a single mechanism tested in a simulated humanoid robot.Vincenzo G. Fiore, Valerio Sperati, Francesco Mannella, Marco Mirolli, Kevin Gurney, Karl Friston, Raymond J. Dolan & Gianluca Baldassarre - 2014 - Frontiers in Psychology 5.
    The effects of striatal dopamine (DA) on behavior have been widely investigated over the past decades, with “phasic” burst firings considered as the key expression of a reward prediction error responsible for reinforcement learning. Less well studied is “tonic” DA, where putative functions include the idea that it is a regulator of vigor, incentive salience, disposition to exert an effort and a modulator of approach strategies. We present a model combining tonic and phasic DA to show how different outflows triggered (...)
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  • Search and the Aging Mind: The Promise and Limits of the Cognitive Control Hypothesis of Age Differences in Search.Rui Mata & Bettina Helversen - 2015 - Topics in Cognitive Science 7 (3):416-427.
    Search is a prerequisite for successful performance in a broad range of tasks ranging from making decisions between consumer goods to memory retrieval. How does aging impact search processes in such disparate situations? Aging is associated with structural and neuromodulatory brain changes that underlie cognitive control processes, which in turn have been proposed as a domain-general mechanism controlling search in external environments as well as memory. We review the aging literature to evaluate the cognitive control hypothesis that suggests that age-related (...)
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