Search results for "Associative Self-Organizing Map"

showing 4 items of 4 documents

How do we understand other's intentions? - An implementation of mindreading in artificial systems -

SOM Self-Organizing Map A-SOM Associative Self-Organizing Map NN Neural Network AR Action Recognition HM Hierarchical models IU Intention Understanding HRI Human Robot Interaction
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Simulating music with associative self-organizing maps

2018

Abstract We present an architecture able to recognise pitches and to internally simulate likely continuations of partially heard melodies. Our architecture consists of a novel version of the Associative Self-Organizing Map (A-SOM) with generalized ancillary connections. We tested the performance of our architecture with melodies from a publicly available database containing 370 Bach chorale melodies. The results showed that the architecture could learn to represent and perfectly simulate the remaining 20% of three different interrupted melodies when using a context length of 8 centres of activity in the A-SOM. These promising and encouraging results show that our architecture offers somethi…

MelodySelf-organizing mapComputer scienceCognitive NeuroscienceExperimental and Cognitive PsychologyContext (language use)02 engineering and technologycomputer.software_genre050105 experimental psychologyArtificial Intelligence0202 electrical engineering electronic engineering information engineering0501 psychology and cognitive sciencesInternal simulationArchitectureAssociative propertySettore ING-INF/05 - Sistemi Di Elaborazione Delle Informazionibusiness.industry05 social sciencesInformation and Computer ScienceNeural networkAssociative self-organizing map020201 artificial intelligence & image processingArtificial intelligencebusinesscomputerMusicNatural language processingBiologically Inspired Cognitive Architectures
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Simulating Actions with the Associative Self-Organizing Map

2013

We present a system that can learn to represent actions as well as to internally simulate the likely continuation of their initial parts. The method we propose is based on the Associative Self Organizing Map (A-SOM), a variant of the Self Organizing Map. By emulating the way the human brain is thought to perform pattern recognition tasks, the A- SOM learns to associate its activity with di erent inputs over time, where inputs are observations of other's actions. Once the A-SOM has learnt to recognize actions, it uses this learning to predict the continuation of an observed initial movement of an agent, in this way reading its intentions. We evaluate the system's ability to simulate actions …

Associative Self-Organizing Map Neural Network Action Recognition Internal Simulation Intention Understanding
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Internal Simulation of an Agent’s Intentions

2013

We present the Associative Self-Organizing Map (A-SOM) and propose that it could be used to predict an agent’s intentions by internally simulating the behaviour likely to follow initial movements. The A-SOM is a neural network that develops a representation of its input space without supervision, while simultaneously learning to associate its activity with an arbitrary number of additional (possibly delayed) inputs. We argue that the A-SOM would be suitable for the prediction of the likely continuation of the perceived behaviour of an agent by learning to associate activity patterns over time, and thus a way to read its intentions.

Associative Self-Organizing Map; Internal Simulation;ContinuationArtificial neural networkbusiness.industryComputer scienceAssociative Self-Organizing MapRepresentation (systemics)Artificial intelligenceSpace (commercial competition)businessInternal SimulationAssociative property
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