Cognitive science has much to contribute to the general scientific body of knowledge, but it is also a field rife with possibilities for providing background research that can be leveraged by artificial intelligence (AI) developers. In this introduction, we briefly explore the history of AI. We particularly focus on the relationship between AI and cognitive science and introduce this special issue

A diverse set of topics is assembled in the current issue of Topics in Cognitive Science: An overview of award-winning research in the Fellows topic, a content topic on rationality, and a contribution to a debate that has engaged many in and beyond cognitive science. The topic devoted to the Fellows of the Cognitive Science Society was initiated in 2021 to provide all Fellows of the Society with an

Most computational theories of cognition lack a representation of physiology. Understanding the cognitive effects of compounds present in the environment is important for explaining and predicting changes in cognition and behavior given exposure to toxins, pharmaceuticals, or the deprivation of critical compounds like oxygen. This research integrates physiologically based pharmacokinetic (PBPK) model

We describe a new approach for developing and validating cognitive process models. In our methodology, graphical models (specifically, hidden Markov models) are developed both from human empirical data on a task and synthetic data traces generated by a cognitive process model of human behavior on the task. Differences between the two graphical models can then be used to drive model refinement. We show

Normal aging is typically associated with declines in navigation and spatial memory abilities. However, increased interindividual variability in performance across various navigation/spatial memory tasks is also evident with advancing age. In this review paper, we shed the spotlight on those older individuals who exhibit exceptional, sometimes even youth-like navigational/spatial memory abilities.

The parameters governing our behavior are in constant flux. Accurately capturing these dynamics in cognitive models poses a challenge to modelers. Here, we demonstrate a mapping of ACT-R's declarative memory onto the linear ballistic accumulator (LBA), a mathematical model describing a competition between evidence accumulation processes. We show that this mapping provides a method for inferring individual

In this study, we explore the future of work by examining differences in productivity when teams are composed of only humans or both humans and machine agents. Our objective was to characterize the similarities and differences between human and human–machine teams as they work to coordinate across their specialized roles. This form of research is increasingly important given that machine agents are

This issue of Topics in Cognitive Science offers everyday activities, an argument for the transformative power of cognitive tools, and some of the best papers of last year's CogSci conference. Why bother about how people tackle tasks such as dressing, setting the table, or cleaning up? Because what appears to be trivial actually turns out to be ever so challenging when described and analyzed in terms

During the early postnatal years, most infants rapidly learn to understand two naturally evolved communication systems: language and emotion. While these two domains include different types of content knowledge, it is possible that similar learning processes subserve their acquisition. In this review, we compare the learnable statistical regularities in language and emotion input. We then consider

Recent publications have lamented the dominance of psychology in cognitive science. However, this relies on a limited definition of collaboration between fields. We call for a renewed conception of interdisciplinarity as a “mixture of expertise.” We describe an information-theoretic measure of interdisciplinarity and apply it to multiauthored published articles. Results suggest that cognitive science

Prior research in judgment and decision making (JDM) has investigated the effect of problem framing on human preferences. Furthermore, research in JDM documented the absence of such reversal of preferences when making decisions from experience. However, little is known about the effect of context on preferences under the combined influence of problem framing and problem format. Also, little is known

Consideration of collectives raises important questions about human rationality. This has long been known for questions about preferences, but it holds also with respect to beliefs. For one, there are contexts (such as voting) where we might care as much, or more, about the rationality of a collective than the rationality of the individuals it comprises. Here, a given standard may yield competing assessments

We seek to understand rational decision making and if it exists whether finite (bounded) agents may be able to achieve its principles. This aim has been a singular objective throughout much of human science and philosophy, with early discussions identified since antiquity. More recently, there has been a thriving debate based on differing perspectives on rationality, including adaptive heuristics,

Complex work in teams requires coordination across team members and their technology as well as the ability to change and adapt over time to achieve effective performance. To support such complex interactions, recent efforts have worked toward the design of adaptive human-autonomy teaming systems that can provide feedback in or near real time to achieve the desired individual or team results. However

Spatial ability plays important roles in academic learning and everyday activities. A type of spatial thinking that is of particular significance to people's daily lives is cognitive mapping, that is, the process of acquiring, representing, and using knowledge about spatial environments. However, the skill of cognitive mapping shows large individual differences, and the task of spatial orientation

We propose an account of cognitive tools that takes into account the process of enculturation by which tools are integrated into our cognitive systems. Drawing on work in cultural evolution and developmental psychology, we argue that cognitive tools are complex entities consisting of physical objects, representational systems, and cognitive practices for the physical manipulation of the tool. We use

Navigational performance responds to navigational challenges, and both decline with age in Western populations as older people become less mobile. But mobility does not decline everywhere; Tsimané forager-farmers in Bolivia remain highly mobile throughout adulthood, traveling frequently by foot and dugout canoe for subsistence and social visitation. We, therefore, measured both natural mobility and

The ease with which humans usually perform everyday activities masks their inherit complexity. Tasks such as setting a table prior to a meal or preparing a hot beverage require the coordination of several cognitive abilities. At the same time, many everyday activities are simple enough to afford investigation in controlled lab settings. One main goal of this issue is to raise awareness of everyday

Prior research has demonstrated that trust in robots and performance of robots are two important factors that influence human–autonomy teaming. However, other factors may influence users’ perceptions and use of autonomous systems, such as perceived intent of robots and decision authority of the robots. The current study experimentally examined participants’ trust in an autonomous security robot (ASR)

Research on spatial thinking requires reliable and valid measures of individual differences in various component skills. Spatial perspective taking (PT)—the ability to represent viewpoints different from one's own—is one kind of spatial skill that is especially relevant to navigation. This study had two goals. First, the psychometric properties of four PT tests were examined: Four Mountains Task (FMT)

The ability to anticipate team members' actions enables joint action towards a common goal. Task knowledge and mental simulation allow for anticipating other agents' actions and for making inferences about their underlying mental representations. In human–AI teams, providing AI agents with anticipatory mechanisms can facilitate collaboration and successful execution of joint action. This paper presents

Navigating to goal locations in a known environment (wayfinding) can be accomplished by different strategies, notably by taking habitual, well-learned routes (response strategy) or by inferring novel paths, such as shortcuts, from spatial knowledge of the environment's layout (place strategy). Human and animal neuroscience studies reveal that these strategies reflect different brain systems, with response

Navigation ability varies widely across humans. Prior studies have reported that being younger and a male has an advantage for navigation ability. However, these studies have generally involved small numbers of participants from a handful of western countries. Here, we review findings from our project Sea Hero Quest, which used a video game for mobile and tablet devices to test 3.9 million people on

This year's first issue of Topics in Cognitive Science comprises two very distinct topics: one devoted to a new type of papers authored by a special set of scholars, the Fellows of the Cognitive Science Society, the other being a special issue on an exciting topic, namely an approach to modeling the mind based on network science. Election as Fellow of the Society recognizes a scholar's sustained excellence

Cognitive science is a multidisciplinary field. Whereas debates on whether this is beneficial continue to spring up, this multidisciplinarity comes with at least one obvious challenge, namely, safeguarding an increasing integration across its subfields. The new and open-ended topic preluded here attempts to address this challenge by pursuing a multilayered agenda: to introduce the Fellows of the Cognitive

People undergo many idiosyncratic experiences throughout their lives that may contribute to individual differences in the size and structure of their knowledge representations. Ultimately, these can have important implications for individuals' cognitive performance. We review evidence that suggests a relationship between individual experiences, the size and structure of semantic representations, as

Thinking is complex. Over the years, several types of methods and paradigms have developed across the psychological, cognitive, and neural sciences to study such complexity. A rapidly growing multidisciplinary quantitative field of network science offers quantitative methods to represent complex systems as networks, or graphs, and study the network properties of these systems. While the application

Many of the computational problems people face are difficult to solve under the limited time and cognitive resources available to them. Overcoming these limitations through social interaction is one of the most distinctive features of human intelligence. In this paper, we show that information accumulation in multigenerational social networks can be produced by a form of distributed Bayesian inference

Many everyday activities are sequential in nature. That is, they can be seen as a sequence of subactions and sometimes subgoals. In the motor execution of sequential action, context effects are observed in which later subactions modulate the execution of earlier subactions (e.g., reaching for an overturned mug, people will optimize their grasp to achieve a comfortable end state). A trajectory (movement)

Syllogistic reasoning lies at the intriguing intersection of natural and formal reasoning of language and logic. Syllogisms comprise a formal system of reasoning yet make use of natural language quantifiers (e.g., all, some) and invite natural language conclusions. The conclusions people tend to draw from syllogisms, however, deviate substantially from the purely logical system. Are principles of natural

Over their first years of life, children learn not just the words of their native languages, but how to use them to communicate. Because manual annotation of communicative intent does not scale to large corpora, our understanding of communicative act development is limited to case studies of a few children at a few time points. We present an approach to automatic identification of communicative acts

Improving the accuracy of medical image interpretation can improve the diagnosis of numerous diseases. We compared different approaches to aggregating repeated decisions about medical images to improve the accuracy of a single decision maker. We tested our algorithms on data from both novices (undergraduates) and experts (medical professionals). Participants viewed images of white blood cells and made

The study of human cognition and the study of artificial intelligence (AI) have a symbiotic relationship, with advancements in one field often informing or creating new work in the other. Human cognition has many capabilities modern AI systems cannot compete with. One such capability is the detection, identification, and resolution of knowledge gaps (KGs). Using these capabilities as inspiration, we

In social and service robotics, complex collaborative tasks are expected to be executed while interacting with humans in a natural and fluent manner. In this scenario, the robotic system is typically provided with structured tasks to be accomplished, but must also continuously adapt to human activities, commands, and interventions. We propose to tackle these issues by exploiting the concept of cognitive

In reflexively autocatalytic foodset (RAF)-generated networks, nodes are not only passive transmitters of activation, but they also actively galvanize, or “catalyze” the synthesis of novel (“foodset-derived”) nodes from existing ones (the “foodset”). Thus, RAFs are uniquely suited to modeling how new structure grows out of currently available structure, and analyzing phase transitions in potentially

My first 30-odd years of research in cognitive science has been driven by an attempt to balance two facts about human thought that seem incompatible and two corresponding ways of understanding information processing. The facts are that, on one hand, human memories serve as sophisticated pattern recognition devices with great flexibility and an ability to generalize and predict as long as circumstances

In his 12 years of service as Founding and Executive Editor of Topics in Cognitive Science (topiCS), Wayne Gray had only once hosted a topic of his own, even though he must have been incubating an ever-growing number of ideas, either for themes he was excited about or which he sensed were missing from the collection of topics published by the journal in its first decade. Eventually, as he was stepping

Tasks, tools, and techniques that we perform, use, and acquire, define the elements of expertise which we value as the hallmarks of goal-driven behavior. Somehow, the creation of tools enables us to define new tasks, or is it that the envisioning of new tasks drives us to invent new tools? Or maybe it is that new tools engender new techniques which then result in new tasks? This jumble of issues will

Acquiring expertise in a task is often thought of as an automatic process that follows inevitably with practice according to the log-log law (aka: power law) of learning. However, as Ericsson, Chase, and Faloon (1980) showed, this is not true for digit-span experts and, as we show, it is certainly not true for Tetris players at any level of expertise. Although some people may simply “twitch” faster

Understanding the link between brain evolution and the evolution of distinctive features of modern human cognition is a fundamental challenge. A still unresolved question concerns the co-evolution of tool behavior (i.e., tool use or tool making) and language. The shared neurocognitive processes hypothesis suggests that the emergence of the combinatorial component of language skills within the frontal

Traditional statistics instruction emphasizes a .05 significance level for hypothesis tests. Here, we investigate the consequences of this training for researchers’ mental representations of probabilities — whether .05 becomes a boundary, that is, a discontinuity of the mental number line, and alters their reasoning about p-values. Graduate students with statistical training (n = 25) viewed pairs of

Humans make decisions in dynamic environments (increasingly complex, highly uncertain, and changing situations) by searching for potential alternatives sequentially over time, to determine the best option at a precise moment. Surprisingly, the field of behavioral decision making has little to offer in terms of theoretical principles and practical guidelines on how people make decisions in dynamic situations

Daily function depends on an ability to mentally map our environment. Environmental factors such as visibility and layout, and internal factors such as psychological stress, can challenge spatial memory and efficient navigation. Importantly, people vary dramatically in their ability to navigate flexibly and overcome such challenges. In this paper, we present an overview of “schema theory” and our view

The last two decades have produced unprecedented successes in the fields of artificial intelligence and machine learning (ML), due almost entirely to advances in deep neural networks (DNNs). Deep hierarchical memory networks are not a novel concept in cognitive science and can be traced back more than a half century to Simon's early work on discrimination nets for simulating human expertise. The major

The fields of machine learning (ML) and cognitive science have developed complementary approaches to computationally modeling human behavior. ML's primary concern is maximizing prediction accuracy; cognitive science's primary concern is explaining the underlying mechanisms. Cross-talk between these disciplines is limited, likely because the tasks and goals usually differ. The domain of e-learning and

We argue that cognitive models can provide a common ground between human users and deep reinforcement learning (Deep RL) algorithms for purposes of explainable artificial intelligence (AI). Casting both the human and learner as cognitive models provides common mechanisms to compare and understand their underlying decision-making processes. This common grounding allows us to identify divergences and

A problem is a situation in which an agent seeks to attain a given goal without knowing how to achieve it. Human problem solving is typically studied as a search in a problem space composed of states (information about the environment) and operators (to move between states). A problem such as playing a game of chess has possible states, and a traveling salesperson problem with as little as 82 cities

We examine the mechanisms required to handle everyday activities from the standpoint of cognitive robotics, distinguishing activities on the basis of complexity and transparency. Task complexity (simple or complex) reflects the intrinsic nature of a task, while task transparency (easy or difficult) reflects an agent's ability to identify a solution strategy in a given task. We show how the CRAM cognitive

Cognitive researchers often carve cognition up into structures and processes. Cognitive processes operate on structures, like vehicles driving over a map. Language alongside semantic and episodic memory are proposed to have structure, as are perceptual systems. Over these structures, processes operate to construct memory and solve problems by retrieving and manipulating information. Network science

Individuals vary in the way they navigate through space. Some take novel shortcuts, while others rely on known routes to find their way around. We wondered how and why there is so much variation in the population. To address this, we first compared the trajectories of 368 human subjects navigating a virtual maze with simulated trajectories. The simulated trajectories were generated by strategy-based

Goal-directed behavior is a deeply important part of human psychology. People constantly set goals for themselves and pursue them in many domains of life. In this paper, we develop computational models that characterize how humans pursue goals in a complex dynamic environment and test how well they describe human behavior in an experiment. Our models are motivated by the principle of resource rationality

Ecological rationality represents an alternative to classic frameworks of rationality. Extending on Herbert Simon's concept of bounded rationality, it holds that cognitive processes, including simple heuristics, are not per se rational or irrational, but that their success rests on their degree of fit to relevant environmental structures. The key is therefore to understand how cognitive and environmental

Our earliest tools are our bodies. Our hands raise and turn and toss and carry and push and pull, our legs walk and climb and kick allowing us to move and act in the world and to create the multitude of artifacts that improve our lives. The list of actions made by our hands and feet and other parts of our bodies is long. What is more remarkable is we turn those actions in the world into actions on

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