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We examine the problem of weaknesses in frameworks of conceptual modeling for handling certain aspects of the system being modeled. We propose the use of a flow-based modeling methodology at the conceptual level. Specifically, and without…

Computers and Society · Computer Science 2017-09-13 Sabah Al-Fedaghi , Abdulaziz AlQallaf

We discuss philosophical issues concerning the notion of cognition basing ourselves in experimental results in cognitive sciences, especially in computer simulations of cognitive systems. There have been debates on the "proper" approach for…

Artificial Intelligence · Computer Science 2007-05-23 Carlos Gershenson

A robot operating in isolation needs to reason over the uncertainty in its model of the world and adapt its own actions to account for this uncertainty. Similarly, a robot interacting with people needs to reason over its uncertainty over…

Robotics · Computer Science 2017-08-07 Stefanos Nikolaidis , Jodi Forlizzi , David Hsu , Julie Shah , Siddhartha Srinivasa

The hypothesis considered here is that cognition is based on a small set of systems-level computational primitives that are defined at a level higher than single neurons. It is pointed out that for one such set of primitives, whose…

Neurons and Cognition · Quantitative Biology 2018-07-30 Leslie Valiant

Computation, the use of a computer to solve, simulate, or visualize a physical problem, has revolutionized how physics research is done. Computation is used widely to model systems, to simulate experiments, and to analyze data. Yet, in most…

Physics Education · Physics 2015-11-18 Marcos D. Caballero

Approaching limitations of digital computing technologies have spurred research in neuromorphic and other unconventional approaches to computing. Here we argue that if we want to systematically engineer computing systems that are based on…

Emerging Technologies · Computer Science 2023-08-21 Herbert Jaeger , Beatriz Noheda , Wilfred G. van der Wiel

In this paper, we make a review on the concepts of rationality across several different fields, namely in economics, psychology and evolutionary biology and behavioural ecology. We review how processes like natural selection can help us…

Artificial Intelligence · Computer Science 2018-12-03 Catarina Moreira

Computational psychiatry is a field aimed at developing formal models of information processing in the human brain, and how alterations in this processing can lead to clinical phenomena. Despite significant progress in the development of…

Neurons and Cognition · Quantitative Biology 2023-01-12 David Benrimoh , Victoria Fisher , Catalina Mourgues , Andrew D. Sheldon , Ryan Smith , Albert R. Powers

Despite differing from the human language processing mechanism in implementation and algorithms, current language models demonstrate remarkable human-like or surpassing language capabilities. Should computational language models be employed…

Computation and Language · Computer Science 2024-03-21 Shaonan Wang , Jingyuan Sun , Yunhao Zhang , Nan Lin , Marie-Francine Moens , Chengqing Zong

As revealed by discussions of principle on energy dissipation by computers, logic imposes constraints on physical systems designed for a logical function. We define a notion of logical dissipation for a finite automaton. We discuss the…

Quantum Physics · Physics 2007-05-23 Philippe Matherat , Marc-Thierry Jaekel

Those designing autonomous systems that interact with humans will invariably face questions about how humans think and make decisions. Fortunately, computational cognitive science offers insight into human decision-making using tools that…

Artificial Intelligence · Computer Science 2021-09-02 Mark K. Ho , Thomas L. Griffiths

The "easy" problem of cognitive science is explaining how and why we can do what we can do. The "hard" problem is explaining how and why we feel. Turing's methodology for cognitive science (the Turing Test) is based on doing: Design a model…

Artificial Intelligence · Computer Science 2012-06-19 Stevan Harnad

Human cognition is theorized to operate in two modes: fast, intuitive System 1 thinking and slow, deliberate System 2 thinking. While current Large Reasoning Models (LRMs) excel at System 2 thinking, their inability to perform fast thinking…

Computation and Language · Computer Science 2025-10-31 Zhengkai Lin , Zhihang Fu , Ze Chen , Chao Chen , Liang Xie , Wenxiao Wang , Deng Cai , Zheng Wang , Jieping Ye

Encoding and decoding models are widely used in systems, cognitive, and computational neuroscience to make sense of brain-activity data. However, the interpretation of their results requires care. Decoding models can help reveal whether…

Neurons and Cognition · Quantitative Biology 2019-04-29 Nikolaus Kriegeskorte , Pamela K. Douglas

A model of knowledge representation is described in which propositional facts and the relationships among them can be supported by other facts. The set of knowledge which can be supported is called the set of cognitive units, each having…

Artificial Intelligence · Computer Science 2013-04-12 A. Julian Craddock , Roger A. Browse

Scientific knowledge expands by observing the world, hypothesizing some theories about it, and testing them against collected data. When those theories take the form of statistical models, statistical analyses are involved in the process of…

Machine Learning · Statistics 2026-03-11 Arnaud Delaunoy

Whether in groups of humans or groups of computer agents, collaboration is most effective between individuals who have the ability to coordinate on a joint strategy for collective action. However, in general a rational actor will only…

Artificial Intelligence · Computer Science 2016-02-15 Peter M. Krafft , Chris L. Baker , Alex Pentland , Joshua B. Tenenbaum

Reasoning is a fundamental aspect of human intelligence that plays a crucial role in activities such as problem solving, decision making, and critical thinking. In recent years, large language models (LLMs) have made significant progress in…

Computation and Language · Computer Science 2023-05-29 Jie Huang , Kevin Chen-Chuan Chang

We describe collective-move Monte Carlo algorithms designed to approximate the overdamped dynamics of self-assembling nanoscale components equipped with strong, short-ranged and anisotropic interactions. Conventional Monte Carlo simulations…

Statistical Mechanics · Physics 2012-04-16 Stephen Whitelam

Often models for understanding the impact of management practices on retail performance are developed under the assumption of stability, equilibrium and linearity, whereas retail operations are considered in reality to be dynamic,…

Artificial Intelligence · Computer Science 2010-07-05 Peer-Olaf Siebers , Uwe Aickelin , Helen Celia , Chris Clegg