The Numenta Platform for Intelligent Computing (NuPIC) is a recently released software, available free for academic purposes. It is based on the Hierarchical Temporal Memory (HTM) paradigm. HTM takes the human neocortex as a computational model.

NuPIC allows for the development and training of HTM applications. Target applications include vision systems, robotics, data mining and analysis, and failure analysis and prediction.

Seems to be worth taking a look into it. The downloads are available here.

Taking them from Wikipedia is not a guarantee of anything, so we should be able to give better (and more adjusted) definitions after crawling into the state of the art a bit more.

Cognition:

The term cognition is used in different ways by different disciplines. In psychology, it refers to an information processing view of an individual’s psychological functions. Other interpretations of the meaning of cognition link it to the development of concepts; individual minds, groups, organizations, and even larger coalitions of entities, can be modelled as societies which cooperate to form concepts. The autonomous elements of each ‘society‘ would have the opportunity to demonstrate emergent behavior in the face of some crisis or opportunity. Cognition can also be interpreted as “understanding and trying to make sense of the world”.

Cognitive science:

Cognitive science is most simply defined as the scientific study either of mind or of intelligence. ^[1] It is an interdisciplinary study drawing from relevant fields including psychology, philosophy, neuroscience, linguistics,anthropology, computer science, and biology. The term cognitive science was coined by Christopher Longuet-Higginsin his 1973 commentary on the Lighthill report, which concerned the then-current state of Artificial Intelligenceresearch. In the same decade, the journal Cognitive Science^[2] and the Cognitive Science Society began.

Cognitive architecture:

A cognitive architecture is a blueprint for intelligent agents. It proposes (artificial) computational processes that act like certain cognitive systems, most often, like a person, or actsintelligent under some definition. Cognitive architectures form a subset of general agent architectures. The term ‘architecture’ implies an approach that attempts to model not only behavior, but also structural properties of the modelled system. These need not be physical properties: they can be properties of virtual machines implemented in physical machines (e.g. brains or computers).

Cognitive model:

A cognitive model is an approximation to animal cognitive processes (predominantly human) for the purposes of comprehension and prediction. Cognitive models can be developed within or without a cognitive architecture, though the two are not always easily distinguishable.

In contrast to cognitive architectures, cognitive models tend to be focused on a single cognitive phenomenon or process (e.g., list learning), how two or more processes interact (e.g., visual search and decision making), or to make behavioral predictions for a specific task or tool (e.g., how instituting a new software package will affect productivity). Cognitive architectures tend to be focused on the structural properties of the modeled system, and help constrain the development of cognitive models within the architecture. Likewise, model development helps to inform limitations and shortcomings of the architecture. Some of the most popular architectures for cognitive modeling include ACT-R and Soar.

Postgrado Psicología de la creatividad :: UAB Barcelona (España)

Filosofía de la mente y de la ciencia cognitiva – 9788446022299 – LaCentral – Barcelona – 2008

Master oficial màster en ciència cognitiva i llenguatge en barcelona – emagister.com

Master in artificial intelligence en barcelona – emagister.com

CCiL – Programa de Doctorat “Ciència, Cognitiva i Llenguatge” (UAB, UB, UPF, URV, UdG)

Departament de Traducció i Filologia

Logos – Logic, Language and Cognition Research Group

GRNC, Grup de Recerca Neurociència Cognitiva

Investigación – BrainLab

Universitat Pompeu Fabra – Departament d’Humanitats

Projectes | CLiC

Cognitive model – Wikipedia, the free encyclopedia

ACT-R – Wikipedia, the free encyclopedia

Soar (cognitive architecture) – Wikipedia, the free encyclopedia

Allen Newell – Wikipedia, the free encyclopedia

CLARION (cognitive architecture) – Wikipedia, the free encyclopedia

EPIC (cognitive architecture) – Wikipedia, the free encyclopedia

Cognitive architecture – Wikipedia, the free encyclopedia

Psi-Theory – Wikipedia, the free encyclopedia

IABG – Verteidigung – Human Factors

The PSI model of emotion, personality and action

Duality of the Mind: A Bottom-Up … – Búsqueda de libros de Google

Herbert Simon – Wikipedia, the free encyclopedia

Unified theory of cognition – Wikipedia, the free encyclopedia

Másters Ciencia Cognitiva y Lenguaje – UAB Barcelona

CCiL – Programa de Doctorat “Ciència, Cognitiva i Llenguatge” (UAB, UB, UPF, URV, UdG)

Màster en ciència cognitiva i llenguatge

Pilar Prieto Currículum

Artificial consciousness – Wikipedia, the free encyclopedia

The CLARION Project — Prof. Ron Sun

Presentation Abstracts for Architecture Symposium

The EPIC Architecture

Deadline 27th April
The symposium welcomes submissions of original papers addressing topics in
both areas of intelligent and distributed computing ranging from concepts
and theoretical developments to advanced technologies and innovative
applications. Papers acceptance and publication will be judged based on
their relevance to the symposium theme, clarity of presentation,
originality and accuracy of results and proposed solutions. Topics
include, but are not limited to, broadly understood:
- Intelligent service composition and orchestration
- E-service and Web intelligence
- Multi-agent systems
- Information extraction and retrieval in distributed environments
- Data mining and knowledge discovery in distributed environments
- Semantic and knowledge grids
- Intelligent integration of data and processes
- Distributed problem solving
- Ontologies and meta-data for describing heterogeneous resources and
services
- Autonomic and adaptive distributed computing
- Intelligence in mobile and ubiquitous computing
- Intelligence in cooperative information systems, groupware and
workflows, virtual enterprises, social networks
- Intelligent applications in e-business/e-commerce, e-learning, e-health,
e-science, e-government
- Self-organising and adaptive distributed systems
- Intelligence in Peer-to-Peer systems
- Emerging behaviours in complex distributed systems
- Modelling and simulation of intelligent distributed systems

http://idc08.diit.unict.it