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Biologically Inspired Cognitive Architectures 2011 Print E-mail
Sunday, 13 November 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.

In this event we presented a general model of emotion based on the interpretation of emotional processes as control reorganisations driven by values.

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Concurrent control patterns deployed over neural components.

Adaptive systems use feedback as a key strategy to cope with uncertainty and change in their environments. The information fed back from the sensorimotor loop into the control architecture can be used to change different elements of the controller at four different levels: parameters of the control model, the control model itself, the functional organization of the agent and the functional components of the agent. The complexity of such a space of potential configurations is daunting. The only viable alternative for the agent –in practical, economical, evolutionary terms– is the reduction of the dimensionality of the configuration space.

This reduction is achieved both by functionalisation –or, to be more precise, by interface minimization– and by patterning, i.e. the selection among a predefined set of organisational configurations. This last analysis let us state the central problem of how autonomy emerges from the integration of the cognitive, emotional and autonomic systems in strict functional terms: autonomy is achieved by the closure of functional dependency.

This talk shows a general model of how the emotional biological systems operate following this theoretical analysis and how this model is also of applicability to a wide spectrum of artificial systems.

Get the slides of the talk.

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