共查询到20条相似文献，搜索用时 15 毫秒
1.
Salvucci DD 《Cognitive Science》2005,29(3):457-492
As cognitive architectures move to account for increasingly complex real-world tasks, one of the most pressing challenges involves understanding and modeling human multitasking. Although a number of existing models now perform multitasking in real-world scenarios, these models typically employ customized executives that schedule tasks for the particular domain but do not generalize easily to other domains. This article outlines a general executive for the Adaptive Control of Thought–Rational (ACT–R) cognitive architecture that, given independent models of individual tasks, schedules and interleaves the models' behavior into integrated multitasking behavior. To demonstrate the power of the proposed approach, the article describes an application to the domain of driving, showing how the general executive can interleave component subtasks of the driving task (namely, control and monitoring) and interleave driving with in-vehicle secondary tasks (radio tuning and phone dialing). 相似文献
2.
CORTEX is a cognitive robotics architecture inspired by three key ideas: modularity, internal modelling and graph representations. CORTEX is also a computational framework designed to support early forms of intelligence in real world, human interacting robots, by selecting an a priori functional decomposition of the capabilities of the robot. This set of abilities was then translated to computational modules or agents, each one built as a network of software interconnected components. The nature of these agents can range from pure reactive modules connected to sensors and/or actuators, to pure deliberative ones, but they can only communicate with each other through a graph structure called Deep State Representation (DSR). DSR is a short-term dynamic representation of the space surrounding the robot, the objects and the humans in it, and the robot itself. All these entities are perceived and transformed into different levels of abstraction, ranging from geometric data to high-level symbolic relations such as “the person is talking and gazing at me”. The combination of symbolic and geometric information endows the architecture with the potential to simulate and anticipate the outcome of the actions executed by the robot. In this paper we present recent advances in the CORTEX architecture and several real-world human-robot interaction scenarios in which they have been tested. We describe our interpretation of the ideas inspiring the architecture and the reasons why this specific computational framework is a promising architecture for the social robots of tomorrow. 相似文献
3.
The mental rotation ability is an essential spatial reasoning skill in human cognition and has proven to be an essential predictor of mathematical and STEM skills, critical and computational thinking. Despite its importance, little is known about when and how mental rotation processes are activated in games explicitly targeting spatial reasoning tasks. In particular, the relationship between spatial abilities and TetrisTM has been analysed several times in the literature. However, these analyses have shown contrasting results between the effectiveness of Tetris-based training activities to improve mental rotation skills. In this work, we studied whether, and under what conditions, such ability is used in the TetrisTM game by explicitly modelling mental rotation via an ACT-R based cognitive model controlling a virtual agent. The obtained results show meaningful insights into the activation of mental rotation during game dynamics. The study suggests the necessity to adapt game dynamics in order to force the activation of this process and, therefore, can be of inspiration to design learning activities based on TetrisTM or re-design the game itself to improve its educational effectiveness. 相似文献
4.
We present a detailed process theory of the moment-by-moment working-memory retrievals and associated control structure that subserve sentence comprehension. The theory is derived from the application of independently motivated principles of memory and cognitive skill to the specialized task of sentence parsing. The resulting theory construes sentence processing as a series of skilled associative memory retrievals modulated by similarity-based interference and fluctuating activation. The cognitive principles are formalized in computational form in the Adaptive Control of Thought–Rational (ACT–R) architecture, and our process model is realized in ACT–R. We present the results of 6 sets of simulations: 5 simulation sets provide quantitative accounts of the effects of length and structural interference on both unambiguous and garden-path structures. A final simulation set provides a graded taxonomy of double center embeddings ranging from relatively easy to extremely difficult. The explanation of center-embedding difficulty is a novel one that derives from the model' complete reliance on discriminating retrieval cues in the absence of an explicit representation of serial order information. All fits were obtained with only 1 free scaling parameter fixed across the simulations; all other parameters were ACT–R defaults. The modeling results support the hypothesis that fluctuating activation and similarity-based interference are the key factors shaping working memory in sentence processing. We contrast the theory and empirical predictions with several related accounts of sentence-processing complexity. 相似文献
5.
This fMRI study examines the changes in participants’ information processing as they repeatedly solve the same mathematical problem. We show that the majority of practice-related speedup is produced by discrete changes in cognitive processing. Because the points at which these changes take place vary from problem to problem, and the underlying information processing steps vary in duration, the existence of such discrete changes can be hard to detect. Using two converging approaches, we establish the existence of three learning phases. When solving a problem in one of these learning phases, participants can go through three cognitive stages: Encoding, Solving, and Responding. Each cognitive stage is associated with a unique brain signature. Using a bottom-up approach combining multi-voxel pattern analysis and hidden semi-Markov modeling, we identify the duration of that stage on any particular trial from participants brain activation patterns. For our top-down approach we developed an ACT-R model of these cognitive stages and simulated how they change over the course of learning. The Solving stage of the first learning phase is long and involves a sequence of arithmetic computations. Participants transition to the second learning phase when they can retrieve the answer, thereby drastically reducing the duration of the Solving stage. With continued practice, participants then transition to the third learning phase when they recognize the problem as a single unit and produce the answer as an automatic response. The duration of this third learning phase is dominated by the Responding stage. 相似文献
6.
John R. Anderson 《Cognitive Science》2002,26(1):85-112
Much of cognitive psychology focuses on effects measured in tens of milliseconds while significant educational outcomes take tens of hours to achieve. The task of bridging this gap is analyzed in terms of Newell's (1990) bands of cognition—the Biological, Cognitive, Rational, and Social Bands. The 10 millisecond effects reside in his Biological Band while the significant learning outcomes reside in his Social Band. The paper assesses three theses: The Decomposition Thesis claims that learning occurring at the Social Band can be reduced to learning occurring at lower bands. The Relevance Thesis claims that instructional outcomes at the Social Band can be improved by paying attention to cognition at the lower bands. The Modeling Thesis claims that cognitive modeling provides a basis for bridging between events on the small scale and desired outcomes on the large scale. The unit‐task level, at the boundary of the Cognitive and Rational Bands, is useful for assessing these theses. There is good evidence for all three theses in efforts that bridge from the unit‐task level to educational applications. While there is evidence for the Decomposition Thesis all the way down to the 10 millisecond level, more work needs to be done to establish the Relevance Thesis and particularly the Modeling Thesis at the lower levels. 相似文献
7.
《Philosophical Psychology》2012,25(2):199-220
Cognitive architectures—task-general theories of the structure and function of the complete cognitive system—are sometimes argued to be more akin to frameworks or belief systems than scientific theories. The argument stems from the apparent non-falsifiability of existing cognitive architectures. Newell was aware of this criticism and argued that architectures should be viewed not as theories subject to Popperian falsification, but rather as Lakatosian research programs based on cumulative growth. Newell's argument is undermined because he failed to demonstrate that the development of Soar, his own candidate architecture, adhered to Lakatosian principles. This paper presents detailed case studies of the development of two cognitive architectures, Soar and ACT-R, from a Lakatosian perspective. It is demonstrated that both are broadly Lakatosian, but that in both cases there have been theoretical progressions that, according to Lakatosian criteria, are pseudo-scientific. Thus, Newell's defense of Soar as a scientific rather than pseudo-scientific theory is not supported in practice. The ACT series of architectures has fewer pseudo-scientific progressions than Soar, but it too is vulnerable to accusations of pseudo-science. From this analysis, it is argued that successive versions of theories of the human cognitive architecture must explicitly address five questions to maintain scientific credibility. 相似文献
8.
Anderson JR Carter CS Fincham JM Qin Y Ravizza SM Rosenberg-Lee M 《Cognitive Science》2008,32(8):1323-1348
This article investigates the potential of fMRI to test assumptions about different components in models of complex cognitive tasks. If the components of a model can be associated with specific brain regions, one can make predictions for the temporal course of the BOLD response in these regions. An event-locked procedure is described for dealing with temporal variability and bringing model runs and individual data trials into alignment. Statistical methods for testing the model are described that deal with the scan-to-scan correlations in the errors of measurement of the BOLD signal. This approach is illustrated using a \"sacrificial\" ACT-R model that involves mapping 6 modules onto 6 brain regions in an experiment from Ravizza, Anderson, and Carter (in press) concerned with equation solving. The model's visual encoding predicted the BOLD response in the fusiform gyrus, its controlled retrieval predicted the BOLD response in the lateral inferior prefrontal cortex, and its subgoal setting predicted the BOLD response in the anterior cingulate cortex. On the other hand, its motor programming failed to predict anticipatory activation in the motor cortex, its representational changes failed to predicted the pattern of activity in the posterior parietal cortex, and its procedural component failed to predict an initial spike in caudate. The results illustrate the power of such data to direct the development of a theory of complex problem solving, both at the level of a specific task model as well as at the level of the cognitive architecture. 相似文献
9.
The development of lateral control skills is crucial to driving safety. The current study examined a computational method using a cognitive architecture to model the learning process of vehicle lateral control. In a fixed-base driving simulator, an experiment compared the lateral control performance of non-drivers, novices, and experienced drivers. A cognitive model using Adaptive Control of Thought-Rational (ACT-R) was built to model the learning process of lateral control skills. The modeling results were compared with the human results. The drivers with more experience had better lateral control performance. The model produced similar results as the human results and modeled the progress of learning. The model provided a computational explanation for the mechanisms of lateral control skill learning. Implication and future studies were discussed. 相似文献
10.
This position paper explores the possible contributions to the science of psychology from insights obtained by building and experimenting with cognitive robots. First, the functional modeling characteristic of experimental psychology is discussed. Second, the computational modeling required for cognitive robotics is described, and possible experiments with them are illustrated. Next, we argue that cognitive developmental robots, robots that “live” through a development phase where they learn about their environments in several different modes, can provide additional benefits to the science of psychology. Finally, the reciprocal interactions between computational modeling/cognitive robotics and functional modeling/experimental psychology are explored. We conclude that each can contribute significantly to the other. 相似文献
11.
The way in which artificial intelligence has developed over the last 50 years has had a major role in shaping cognitive science as it is today. This has generated computational models of behaviour. The connectionist revival of the 1980s added a tinge of neurodynamics to this. Here I suggest that some post-connectionist work in artificial intelligence is turning towards an understanding and formalisation of the mechanisms of brain architectures which contribute to an emergence of cognition providing a closer link between brain mechanisms and experienced brain states. This even addresses the neurological basis of consciousness. 相似文献
12.
Cognitive architectures serve as both unified theories of the mind and as computational infrastructures for constructing intelligent agents. In this article, we review the evolution of one such framework, Icarus, over the three decades of its development. We discuss the representational and processing assumptions made by different versions of the architecture, their relation to alternative theories, and some promising directions for future research. 相似文献
13.
Working memory can be a major source of interference in dual tasking. However, there is no consensus on whether this interference is the result of a single working memory bottleneck, or of interactions between different working memory components that together form a complete working-memory system. We report a behavioral and an fMRI dataset in which working memory requirements are manipulated during multitasking. We show that a computational cognitive model that assumes a distributed version of working memory accounts for both behavioral and neuroimaging data better than a model that takes a more centralized approach. The model’s working memory consists of an attentional focus, declarative memory, and a subvocalized rehearsal mechanism. Thus, the data and model favor an account where working memory interference in dual tasking is the result of interactions between different resources that together form a working-memory system. 相似文献
14.
《Revue Européene de Psychologie Appliquée》2020,70(2):100521
IntroductionRecent research on human–robot interactions (HRI) emphasizes a role of user's attitudes in perceiving robot's with different robot embodiments of varying levels of human likenesses. However, other human factors such as educational background may also help understanding of what conditions contribute to enhance social perception of robot's features.ObjectivesThis study aimed to determine how people's attitudes towards and familiarization with robots influence social perception of particular features of robots.MethodFirst, we measured attitudes towards robots among undergraduate students with diverse educational background (engineering vs. psychology). Then, participants were presented with short movies showing the behaviour of three robots with different levels of sociability. Finally, participants evaluated the characteristics of these robots on a scale.ResultsPeople more familiar with social robots and with more positive attitudes towards them evaluate robots with human traits more highly.ConclusionHuman perception of social robots resembles social phenomena related to human perception of other people. 相似文献
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Constitutive autonomy is the capacity of an entity to perpetually develop its individual constitution and coupling with its environment. We argue that computational entities (i.e., entities that can perform computation) can gain constitutive autonomy through motorsensory self-programming – a mechanism by which the entity acquires new computational processes as a series of patterns of interaction that the entity can learn through experience, simulate internally, and enact in the environment. Motorsensory self-programming allows the evolution of the cognitive coupling between the entity’s behavior selection mechanism and the environment as it appears from the viewpoint of the behavior selection mechanism. Constitutive autonomy of computational entities could lead to genuine agency. 相似文献
17.
In this work, we discuss methodologies and implementation choices to enable a humanoid robot to estimate patients’ mood and emotions during postoperative home rehabilitation. The approach is modular and it has been implemented into a SoftBank Pepper robotic architecture; however, the approach is general and it can be easily adapted to other robotic platforms. A sample of an interactive session for the detection of the patient’s affective state is also reported. 相似文献
18.
The term “Cognitive Architectures” indicates both abstract models of cognition, in natural and artificial agents, and the software instantiations of such models which are then employed in the field of Artificial Intelligence (AI). The main role of Cognitive Architectures in AI is that one of enabling the realization of artificial systems able to exhibit intelligent behavior in a general setting through a detailed analogy with the constitutive and developmental functioning and mechanisms underlying human cognition. We provide a brief overview of the status quo and the potential role that Cognitive Architectures may serve in the fields of Computational Cognitive Science and Artificial Intelligence (AI) research. 相似文献
19.
In this paper we propose a computational framework aimed at extending the problem solving capabilities of cognitive artificial agents through the introduction of a novel, goal-directed, dynamic knowledge generation mechanism obtained via a non monotonic reasoning procedure. In particular, the proposed framework relies on the assumption that certain classes of problems cannot be solved by simply learning or injecting new external knowledge in the declarative memory of a cognitive artificial agent but, on the other hand, require a mechanism for the automatic and creative re-framing, or re-formulation, of the available knowledge. We show how such mechanism can be obtained trough a framework of dynamic knowledge generation that is able to tackle the problem of commonsense concept combination. In addition, we show how such a framework can be employed in the field of cognitive architectures in order to overcome situations like the impasse in SOAR by extending the possible options of its subgoaling procedures. 相似文献
20.
The computational theory of cognition, or computationalism, holds that cognition is a form of computation. Two issues related to this view are comprised by the goal of this paper: A) Computing systems are traditionally seen as representational systems, but functional and enactive approaches support non-representational theories; B) Recently, a sociocultural theory against computationalism was proposed with the aim of ontologically reducing computing to cognition. We defend, however, that cognition and computation are in action, thus cognition is just a form of computing and that cognition is the explanatory basis for computation. We state that: 1. Representational theories of computing recurring to intentional content run into metaphysical problems. 2. Functional non-representational theories do not incur this metaphysical problem when describing computing in terms of the abstract machine. 3. Functional theories are consistent with enactive in describing computing machines not in a strictly functional way, but especially in terms of their organization. 4. Enactive cognition is consistent with the computationalism in describing Turing machines as functionally and organizationally closed systems. 5. The cognitive explanatory basis for computing improves the computational theory of cognition. When developed in the human linguistic domain, computer science is seen as a product of human socionatural normative practices, however, cognition is just an explanatory, not ontological, basis for computing. The paper concludes by supporting that computation is in action, that cognition is just one form of computing in the world and the explanatory basis for computation. 相似文献