University of Birmingham > Talks@bham > Artificial Intelligence and Natural Computation seminars > Towards Dynamic Cognitive Systems and Evolving Intelligence

Towards Dynamic Cognitive Systems and Evolving Intelligence

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If you have a question about this talk, please contact Per Kristian Lehre.

Traditionally, the computational (artificial, machine) intelligence has been developed as a mapping of observations, measurements, and sensed data onto structures which albeit complicated where usually with a fixed structure over the time of exploitation of these constructs (models). This is true for neural networks, fuzzy rule-based, probabilistic (e.g. Bayesian, Hidden Markov, Particle filters etc.) models. During the last decade or so a new trend emerged which breaks these assumptions and addresses the problems and the potential that dynamically evolving structures and model constructs (fuzzy rule-based, neural-network, HMM based, etc.). This emerging sub-discipline is called Evolving Systems and it differs from the traditional Evolutionary Computation and Adaptive Systems.

In this talk the problems/challenges, some approaches (specifically for fuzzy rule-based and neuro-fuzzy cases) and a number of applications (including real-life industrial case studies) will be presented. They summarise the experience of the author during last decade or so in development of this emerging area of research. The potential of application of these new results to robotics, autonomous learning and cognition will be placed a special emphasis.

This talk is part of the Artificial Intelligence and Natural Computation seminars series.

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