Search results for " Internal Simulation"

showing 3 items of 3 documents

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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Discriminating and simulating actions with the associative self-organising map

2015

We propose a system able to represent others’ actions as well as to internally simulate their likely continuation from a partial observation. The approach presented here is the first step towards a more ambitious goal of endowing an artificial agent with the ability to recognise and predict others’ intentions. Our approach is based on the associative self-organising map, a variant of the self-organising map capable of learning to associate its activity with different inputs over time, where inputs are processed observations of others’ actions. We have evaluated our system in two different experimental scenarios obtaining promising results: the system demonstrated an ability to learn discrim…

action recognitionArtificial neural networkneural networkbusiness.industryComputer scienceinternal simulationassociative self-organising map; neural network; action recognition; internal simulation; intention understandingassociative self-organising mapSelf organising mapsMachine learningcomputer.software_genreHuman-Computer InteractionContinuationintention understandingArtificial IntelligenceAction recognitionArtificial intelligencebusinesscomputerSoftwareAssociative propertyConnection Science
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