The subsistence technology of forager communities has varied greatly over space and time. This paper (i) reviews briefly the main causal factors the literature identifies as responsible for this variation; (ii) analyzes in some detail the most prominent idea in the literature on spatial variation:Complex technology is an adaptive response to elevated risks of subsistence failure; (iii) it argues that

Dealing with uncertainty and different degrees of frequency and probability is critical in many everyday activities. However, relevant information does not always come in the form of numerical estimates or direct experiences, but is instead obtained through qualitative, rather vague verbal terms (e.g., “the virus often causes coughing” or “the train is likely to be delayed”). Investigating how people

Tools do not just expand our capabilities. They change what we can do, and in doing so, they change who we are. Serena is Serena because of what she can do with a tennis racket. Tiger is Tiger because of what he can do with a golf club. In changing what we can do, tools also change the very way we perceive the spatial layout of the world. Objects beyond arm's reach appear closer when we wield a tool

The ultimate tool, it could be said, is the brain and body. Therefore, a way to understand tool use is to study the brain's control of the body. A more manageable aim is to use the tools of cognitive science to explore the planning of physical actions. Here, I focus on two kinds of physical acts which directly or indirectly involve tool use: producing finger-press sequences, and walking and reaching

With the current issue of Topics in Cognitive Science, we are proud to present award-winning research again, starting off with a scholar's lifetime achievements distinguished by the Rumelhart Prize, then introducing the Best Papers from the 18th International Conference on Cognitive Modeling. The first topic honors Michelene (“Micki”) T. H. Chi (Arizona State University), the 19th recipient of the

Despite decades of research related to teaching and learning, the findings have made little impact on classroom teaching and learning. This paper briefly describes the four existing methods to close this gap, with more extensive analyses of the limitations of one of the four methods, which is to consolidate and distill robust laboratory findings reported over the past decades and attempt to translate

The International Conference on Cognitive Modeling brings together researchers from around the world whose main goal is to build computational systems that reflect the internal processes of the mind. In this issue, we present the four best representative papers on this work from our 18th meeting, ICCM 2020, which was also the first meeting to be held virtually. Two of these papers develop novel techniques

Production-based cognitive models, such as Adaptive Control of Thought-Rational (ACT-R) or Soar agents, have been a popular tool in cognitive science to model sequential decision processes. While the models have been useful in articulating assumptions and predictions of various theories, they unfortunately require a significant amount of hand coding, both with respect to what building blocks cognitive

Post-traumatic stress disorder (PTSD) is a psychiatric disorder often characterized by the unwanted re-experiencing of a traumatic event through nightmares, flashbacks, and/or intrusive memories. This paper presents a neurocomputational model using the ACT-R cognitive architecture that simulates intrusive memory retrieval following a potentially traumatic event (PTE) and predicts hippocampal volume

Neurophysiology and neuroanatomy constrain the set of possible computations that can be performed in a brain circuit. While detailed data on brain microcircuits is sometimes available, cognitive modelers are seldom in a position to take these constraints into account. One reason for this is the intrinsic complexity of accounting for biological mechanisms when describing cognitive function. In this

Vehicle automation and assistance technologies have been touted as a means to reduce traffic collisions by minimizing or eliminating “error-prone” and inefficient human operators. In concept, automation exists on a continuum that includes engaged driving by a human operator augmented by automated support features, vigilant driver monitoring of vehicle behavior with the possibility of driver take-over

To study the human mind is to consider the nature of associations—how are they learned, what are their constituent parts, and how can they be severed or adjusted? The manipulation of associations stands as a pillar of statistical learning (SL) research, which strongly suggests that processes as diverse as word segmentation, learning of grammatical patterns, and event perception can be explained by

Tool use research has suffered from a lack of consistent theoretical frameworks. There is a plethora of tool use definitions and the most widespread ones are so inclusive that the behaviors that fall under them arguably do not have much in common. The situation is aggravated by the prevalence of anecdotes, which have played an undue role in the literature. In order to provide a more rigorous foundation

A major challenge for research in artificial intelligence is to develop systems that can infer the goals, beliefs, and intentions of others (i.e., systems that have theory of mind, ToM). In this research, we propose a cognitive ToM framework that uses a well-known theory of decisions from experience to construct a computational representation of ToM. Instance-based learning theory (IBLT) is used to

We have all had the experience of everyday mistakes like distractedly pouring orange juice into our cereal bowl rather than the milk or inadvertently continuing on our regular route home rather than stopping at the store as we had planned. These so-called "action slips" (Reason, 1984a) are characterized as failures to execute one's intention arising in habitual or highly learned action sequences. This

Our daily lives are composed of several sequential actions that we perform routinely, such as making breakfast, taking a train, and changing clothes. Previous research has demonstrated that a routine system plays a role in performing and controlling repeated sequential actions in familiar situations, and a top-down control system involves the control of the routine system in novel situations. Specifically

The loss of the ability to independently complete activities of daily living, such as meal preparation and household chores, is a defining characteristic of clinical dementia; however, minor difficulties in completing everyday activities emerge in the mild cognitive impairment stage, and even healthy older adults exhibit subtle functional difficulties compared to younger adults. These functional difficulties

Social media are digitalizing massive amounts of users’ cognitions in terms of timelines and emotional content. Such Big Data opens unprecedented opportunities for investigating cognitive phenomena like perception, personality, and information diffusion but requires suitable interpretable frameworks. Since social media data come from users’ minds, worthy candidates for this challenge are cognitive

Some of the earliest work on understanding how concepts are organized in memory used a network-based approach, where words or concepts are represented as nodes, and relationships between words are represented by links between nodes. Over the past two decades, advances in network science and graph theoretical methods have led to the development of computational semantic networks. This review provides

Body representations are known to be dynamically modulated or extended through tool use. Here, we review findings that demonstrate the importance of a user's tool experience or expertise for successful tool embodiment. Examining expert tool users, such as individuals who use tools in professional sports, people who use chopsticks at every meal, or spinal injury patients who use a wheelchair daily,

The primary goal of this essay is to provide a comprehensive overview and analysis of the various relations between material artifacts and the embodied mind. A secondary goal of this essay is to identify some of the trends in the design and use of artifacts. First, based on their functional properties, I identify four categories of artifacts co-opted by the embodied mind, namely (a) embodied artifacts

With a pair of oppositely valenced stimuli, rating the first one sometimes leads to a more extreme evaluation for the second (e.g., if the second is negatively valenced, rating the first stimulus would lead to a more negative rating for the second). We considered an evaluation bias in the case of clinical diagnosis relating to eating disorders. A population sample which included experienced clinical

Scientists studying decision-making often provide a set of choices, each specified with values or distributions of values, and probabilities or distributions of probabilities. For example, “Would you prefer $100 with probability 1.0 or $1 with probability .9 and $1,000 with probability 0.1?” Other decision research examines choices made in the absence of most quantitative information; for example,

A puzzling finding from research on strategical decision making concerns the effect that predictions have on future actions. Simply stating a prediction about an opponent changes the total probability (pooled over predictions) of a player taking a future action compared to not stating any prediction. This is called an interference effect. We first review five different findings of interference effects

The current issue of Topics in Cognitive Science comprises two topics, both of which are devoted to award‐winning research: one to the Rumelhart Prize and one to the Best Papers from the Cognitive Science Society Conference. Our lead topic honors Michael K. Tanenhaus, the eighteenth recipient of the David E. Rumelhart Prize. Tanenhaus received this award in 2018 for transforming “our understanding

It is a great honor to provide this brief introduction to the Special Issue of topiCS honoring Michael K. Tanenhaus and his receipt of the 2018 David E. Rumelhart Prize of the Cognitive Science Society. Michael Tanenhaus is one of the most influential researchers today in cognitive science, especially within the subfield of human language processing. He has made numerous contributions to the study

Computational models of primate vision took a significant advance with David Marr's tripartite separation of the vision enterprise into the problem formulation, algorithm, and neural implementation; however, many subsequent parallel developments in robotics and modeling greatly refined the algorithm descriptions into very distinct levels that complement each other. This review traces the time course

A classic problem in spoken language comprehension is how listeners perceive speech as being composed of discrete words, given the variable time‐course of information in continuous signals. We propose a syllable inference account of spoken word recognition and segmentation, according to which alternative hierarchical models of syllables, words, and phonemes are dynamically posited, which are expected

Is cognitive science interdisciplinary or multidisciplinary? We contribute to this debate by examining the authorship structure and topic similarity of contributions to the Cognitive Science Society from 2000 to 2019. Our analysis focuses on graph theoretic features of the co‐authorship network—edge density, transitivity, and maximum subgraph size—as well as clustering within the space of scientific

Collaboration requires agents to coordinate their behavior on the fly, sometimes cooperating to solve a single task together and other times dividing it up into sub‐tasks to work on in parallel. Underlying the human ability to collaborate is theory‐of‐mind (ToM), the ability to infer the hidden mental states that drive others to act. Here, we develop Bayesian Delegation, a decentralized multi‐agent

Learning by instruction is one of the most common forms of learning, and a number of research efforts have modeled the cognitive process of instruction following, with many successes. However, most computational models remain brittle with respect to the given instructions, and they lack the ability to adapt dynamically to variants of the instructions. This paper aims to illustrate modeling constructs

Contemporary psycholinguistic models place significant emphasis on the cognitive processes involved in the acquisition, recognition, and production of language but neglect many issues related to the representation of language‐related information in the mental lexicon. In contrast, a central tenet of network science is that the structure of a network influences the processes that operate in that system

Routine action sequences can share a great deal of similarity in terms of their stimulus response mappings. As a consequence, their correct execution relies crucially on the ability to preserve contextual and temporal information. However, there are few empirical studies on the neural mechanism and the brain areas maintaining such information. To address this gap in the literature, we recently recorded

Difficulty retrieving information (e.g., words) from memory is prevalent in neurogenic communication disorders (e.g., aphasia and dementia). Theoretical modeling of retrieval failures often relies on clinical data, despite methodological limitations (e.g., locus of retrieval failure, heterogeneity of individuals, and progression of disorder/disease). Techniques from network science are naturally capable

We tend to talk about events, sort them, reason about them, and learn from them as if they were natural entities, endowed with a beginning and an end, with content, structure, and coherence. Yet how exactly do we recognize events as such and determine their boundaries? What allows us to carve them out from the continuous stream of sensorimotor experiences and turn them into meaningful units of conceptual

Cognitive science thrives on the diversity of its (sub‐)disciplines, and topiCS is the ideal journal for bringing the diversity to bear. In this welcome address as its incoming Executive Editor, I outline my view of the journal and my vision for how to sustain its inviting and integrative power.

For our October 2020 issue (Volume 12, Issue 4), we publish two topics. However, before I describe those, I want to note that this is the last issue of topiCS for me as the Founding and Executive Editor of this journal. This introduction is no place to recount all the details of the origin of the journal, but let me begin by saying that it got its final boost during the Governing Board meeting at the

Our minds navigate a continuous stream of sensorimotor experiences, selectively compressing them into events. Event‐predictive encodings and processing abilities have evolved because they mirror interactions between agents and objects—and the pursuance or avoidance of critical interactions lies at the heart of survival and reproduction. However, it appears that these abilities have evolved not only

Decisions concerning proof of facts in criminal law must be rational because of what is at stake, but the decision‐making process must also be cognitively feasible because of cognitive limitations, and it must obey the relevant legal–procedural constraints. In this topic three approaches to rational reasoning about evidence in criminal law are compared in light of these demands: arguments, probabilities

Hebblewhite, Hohwy, and Drummond view the special issue from a machine learning perspective drawing close relations to model‐based, hierarchical reinforcement learning.

To make sense of the world around us, we must be able to segment a continual stream of sensory inputs into discrete events. In this review, I propose that in order to comprehend events, we engage hierarchical generative models that “reverse engineer” the intentions of other agents as they produce sequential action in real time. By generating probabilistic predictions for upcoming events, generative

For our July 2020 issue (Volume 12, Issue 3), we publish three topics. The first is a one‐paper reply from Rafael Núñez and colleagues entitled, "For the Sciences They are A‐Changin’: A Response to Commentaries on Núñez et al.'s (2019) 'What Happened to Cognitive Science?' " The history of this topic is unusual. It began life as a Nature Human Behavior paper (Núñez et al., 2019) which “accused” the

Recent research in cybersecurity has begun to develop active defense strategies using game‐theoretic optimization of the allocation of limited defenses combined with deceptive signaling. These algorithms assume rational human behavior. However, human behavior in an online game designed to simulate an insider attack scenario shows that humans, playing the role of attackers, attack far more often than

Cognitive modeling involves the creation of computer simulations that emulate the internal processes of the mind. This set of papers are the five best representatives of the papers presented at the 17th International Conference on Cognitive Modeling, ICCM 2019. While they represent a diversity of techniques and tasks, they all also share a striking similarity: They make strong statements about the

People can often learn new tasks quickly. This is hard to explain with cognitive models because they either need extensive task‐specific knowledge or a long training session. In this article, we try to solve this by proposing that task knowledge can be decomposed into skills. A skill is a task‐independent set of knowledge that can be reused for different tasks. As a demonstration, we created an attentional

Averaging performance over a group of individuals implicitly assumes that there is only one set of methods for accomplishing the task and that all learners acquire those methods in the same sequence. We maintain that the average subject is a mythical beast and, rather than profiling a mythical beast, we ask “how do different people each learn the same complex task?” To answer our question, we use SpotLight—a

A model‐based approach for cognitive assistance is proposed to keep track of pilots' changing demands in dynamic situations. Based on model‐tracing with flight deck interactions and EEG recordings, the model is able to represent individual pilots' behavior in response to flight deck alerts. As a first application of the concept, an ACT‐R cognitive model is created using data from an empirical flight

A recent issue of Topics in Cognitive Science featured 11 thoughtful commentaries responding to our article “What happened to cognitive science?” (Núñez et al., 2019). Here, we identify several themes that arose in those commentaries and respond to each. Crucial to understanding our original article is the fundamental distinction between multidisciplinary and interdisciplinary endeavors: Cognitive

Events—the experiences we think we are having and recall having had—are constructed; they are not what actually occurs. What occurs is ongoing dynamic, multidimensional, sensory flow, which is somehow transformed via psychological processes into structured, describable, memorable units of experience. But what is the nature of the redescription processes that fluently render dynamic sensory streams

The challenge of explaining how cognition can be tractably realized is widely recognized. Classical rationality is thought to be intractable due to its assumptions of optimization and/or domain generality, and proposed solutions therefore drop one or both of these assumptions. We consider three such proposals: Resource‐Rationality, the Adaptive Toolbox theory, and Massive Modularity. All three seek

Although the stream of information we encounter is continuous, our experiences tend to be discretized into meaningful clusters, altering how we represent our past. Event segmentation theory proposes that clustering ongoing experience in this way is adaptive in that it promotes efficient online processing as well as later reconstruction of relevant information. A growing literature supports this theory

Cognitive science began as a multidisciplinary endeavor to understand how the mind works. Since the beginning, cognitive scientists have been asking questions about the right methodologies and levels of explanation to pursue this goal, and make cognitive science a coherent science of the mind. Key questions include: Is there a privileged level of explanation in cognitive science? How do different levels

Network neuroscience represents the brain as a collection of regions and inter‐regional connections. Given its ability to formalize systems‐level models, network neuroscience has generated unique explanations of neural function and behavior. The mechanistic status of these explanations and how they can contribute to and fit within the field of neuroscience as a whole has received careful treatment

Model evaluation is commonly performed by relying on aggregated data as well as relative metrics for model comparison and selection. In light of recent criticism about the prevailing perspectives on cognitive modeling, we investigate models for human syllogistic reasoning in terms of predictive accuracy on individual responses. By contrasting cognitive models with statistical baselines such as random

Two topics grace our second issue of Topics in Cognitive Science (topiCS) for 2020; (a) Lying in Logic, Language, and Cognition organized and edited by Hans van Ditmarsch (CNRS), Petra Hendriks (Rijksuniversiteit Groningen), and Rineke Verbrugge (Rijksuniversiteit Groningen), and (b) the Cultural Evolution of Cognition organized and edited by Sieghard Beller (formerly of the University of Bergen, Norway)

This topic addresses a question of key interest to cognitive science, namely which factors may have triggered, constrained, or shaped the course of cognitive evolution. It highlights the relevance of culture as a driving force in this process, with a special focus on social learning and language, conceptual tools, and material culture. In so doing, the topic combines two goals: to provide an overview

Warren and Dresang comment on the contributions from a psycholinguistic perspective, highlighting close relations between the respective research on events and proposing that, for example, verbs may indeed directly pre‐activate templates of the typically involved event participants.

For people to communicate with each other, they must tie, or anchor, each of their utterances to the speaker, addressees, place, time, display, and purpose of that utterance. Doing this takes coordination. Producers must index each of these entities for their addressees, and addressees must identify each of the entities the producers are indexing. When people are face to face, they have a battery of

The unifying theme for the papers in this volume is that event‐predictive representations play an important role in cognitive processes, and they are a particularly fruitful object of study for cognitive scientists. In this paper, we present our own model of event representations that draws together several disparate strands of research into event representations, relating to event perception, event