Cognitive Architecture

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Comparison of cognitive architectures
Copycat (software) Copycat (software) Copycat is a model of analogy making and human cognition based on the concept of the parallel terraced scan, developed in 1988 by Douglas Hofstadter, Melanie Mitchell, and others at the Center for Research on Concepts and Cognition, Indiana University Bloomington. The original Copycat was written in Common Lisp and is bitrotten (as it relies on now-outdated graphics libraries); however, a Java port exists. Copycat produces answers to such problems as "abc is to abd as ijk is to what?" (abc:abd :: ijk:?). Hofstadter and Mitchell consider analogy making as the core of high-level cognition, or high-level perception, as Hofstadter calls it, basic to recognition and categorization. High-level perception emerges from the spreading activity of many independent processes, called codelets, running in parallel, competing or cooperating.
Comparative Repository of Cognitive Architectures
The Emotion Machine: Commonsense Thinking, Artificial Intelligence, and the Future of the Human Mind [1] is a book by cognitive scientist Marvin Lee Minsky. The book is a sequel to Minsky's earlier book Society of Mind. Minsky argues that emotions are different ways to think that our mind uses to increase our intelligence. The Emotion Machine The Emotion Machine
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Structure of Intelligence Table of Contents
The project was started in 1984 by Douglas Lenat at MCC and is developed by the Cycorp company. Parts of the project are released as OpenCyc, which provides an API, RDF endpoint, and data dump under an open source license. Overview[edit] Cyc Cyc
Characterization[edit] Common among researchers on cognitive architectures is the belief that understanding (human, animal or machine) cognitive processes means being able to implement them in a working system, though opinions differ as to what form such a system can have: some researchers assume that it will necessarily be a symbolic computational system whereas others argue for alternative models such as connectionist systems or dynamical systems. Cognitive architectures can be characterized by certain properties or goals, as follows, though there is not general agreement on all aspects: Cognitive architecture Cognitive architecture
Un article de Wikipédia, l'encyclopédie libre. Pour les articles homonymes, voir Réseau. En mathématiques, un réseau de concepts est un graphe entièrement connexe dont les nœuds ont une valeur symbolique (un texte, une chaîne de caractères), et une activation. Les liens entre ces nœuds sont pondérés et orientés, de sorte qu'ils puissent représenter l'influence d'un nœud sur un autre. Définition[modifier | modifier le code] Réseau de concepts Réseau de concepts
Biologically inspired cognitive architectures Biologically Inspired Cognitive Architectures (BICA) was a DARPA project administered by the Information Processing Technology Office (IPTO) which began in 2005 and is designed to create the next generation of Cognitive architecture models of human artificial intelligence. Its first phase (Design) ran from September 2005 to around October 2006, and was intended to generate new ideas for biological architectures that could be used to create embodied computational architectures of human intelligence. The second phase (Implementation) of BICA was set to begin in the spring of 2007, and would have involved the actual construction of new intelligent agents that live and behave in a virtual environment. However, this phase was canceled by DARPA, reportedly because it was seen as being too ambitious.[1] Now BICA is a transdisciplinary study that aims to design, characterise and implement human-level cognitive architectures. Biologically inspired cognitive architectures
Scientists Afflict Computers with Schizophrenia to Better Understand the Human Brain | News May 5, 2011 AUSTIN, Texas — Computer networks that can't forget fast enough can show symptoms of a kind of virtual schizophrenia, giving researchers further clues to the inner workings of schizophrenic brains, researchers at The University of Texas at Austin and Yale University have found. The researchers used a virtual computer model, or "neural network," to simulate the excessive release of dopamine in the brain. They found that the network recalled memories in a distinctly schizophrenic-like fashion. Their results were published in April in Biological Psychiatry. "The hypothesis is that dopamine encodes the importance — the salience — of experience," says Uli Grasemann, a graduate student in the Department of Computer Science at The University of Texas at Austin. Scientists Afflict Computers with Schizophrenia to Better Understand the Human Brain | News
Introduction Introduction JAYET Arnaud Maîtrise de sciences cognitives Année 2002 – 2003
ACT-R ACT-R Most of the ACT-R basic assumptions are also inspired by the progress of cognitive neuroscience, and ACT-R can be seen and described as a way of specifying how the brain itself is organized in a way that enables individual processing modules to produce cognition. Inspiration[edit] What ACT-R looks like[edit]
Neural Network

Examine the delicate branching patterns on a leaf or a dragonfly’s wing and you’ll see a complex network of nested loops. This pattern can be found scattered throughout nature and structural engineering: in the brain’s cerebral vasculature, arrays of fungi living underground, the convoluted shape of a foraging slime mold and the metal bracings of the Eiffel Tower. The Eiffel Tower incorporates many nested loops, designed to distribute strain over the structure. In Natural Networks, Strength in Loops In Natural Networks, Strength in Loops
Ricardo Sanz Home Page - Biologically Inspired Cognitive Architectures 2011 The Biologically Inspired Cognitive Architectures 2011 Conference took place at Washington, USA on 4-6 November 2011. The challenge of creating a real-life computational equivalent of the human mind calls for our joint efforts to better understand at a computational level how natural intelligent systems develop their cognitive and learning functions. BICA conference grew up from a AAAI Fall symposium, focusing on the emergent hot topics in computer, brain and cognitive sciences unified by the challenge of replicating the human mind in a computer.
Autonomous Systems Laboratory - Home An ASLab Research Seminar for Autonomous Systems Ricardo Sanz Place: Aula de Seminarios de Automática Time: December 12, 2013 / 12:30-14:00 Our lives depend on the technical infrastructure that surrounds us. The contemporary -beginnings of XXI century- human ecosystem is composed not just of our preys, our predators, the fruits to gather and the inclement climate.
Hierarchy of Cognitive Architectures
Liste de concepts logiques
Marvin Lee Minsky (born August 9, 1927) is an American cognitive scientist in the field of artificial intelligence (AI), co-founder of Massachusetts Institute of Technology's AI laboratory, and author of several texts on AI and philosophy.[6][7][9][10][11][12][13][14][15][16][17] Biography[edit] Isaac Asimov described Minsky as one of only two people he would admit were more intelligent than he was, the other being Carl Sagan.[22] Probably no one would ever know this; it did not matter. In the 1980s, Minsky and Good had shown how neural networks could be generated automatically—self replicated—in accordance with any arbitrary learning program. Marvin Minsky
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Perceptron The perceptron algorithm was invented in 1957 at the Cornell Aeronautical Laboratory by Frank Rosenblatt.[1] Definition[edit] The perceptron is a binary classifier which maps its input (a real-valued vector) to an output value
Artificial senses