Representations and Models in Psychology

Suppes, Patrick; Mautner, Pavel; Falmagne, Jean‐Claude

doi:10.1146/annurev.ps.45.020194.002505

Cited by 16 publications

(9 citation statements)

References 23 publications

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“…In general, we can associate a numerical significance with the th firing neuron and employ the significance vector (5) to represent the rank-order code. We will generally assume that the significance vector has been normalized, so that (6) An example of this is , which is then scaled to unit length, yielding the normalized significance vector . Thus, all significance vectors lie on the surface of the first quadrant of the unit sphere in an -dimensional space, though their distribution on this surface is far from even-each vector represents a different permutation of the same set of coordinates.…”

Section: A Representing a Rank-order Codementioning

confidence: 99%

“…T HE sparse distributed memory (SDM) [1]- [3] is an interesting form of associative memory [4], popular in both the computer science [5] and psychology [6] literature as it represents both an interesting information storage device and a plausible mathematical model of human long-term memory. The SDM associates two binary vectors and by projecting into a very high-dimensional intermediate vector , and then associating and .…”

Section: Introductionmentioning

confidence: 99%

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Sparse Distributed Memory Using Rank-Order Neural Codes

Furber

Brown

Bose

et al. 2007

IEEE Trans. Neural Netw.

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Abstract-A variant of a sparse distributed memory (SDM) is shown to have the capability of storing and recalling patterns containing rank-order information. These are patterns where information is encoded not only in the subset of neuron outputs that fire, but also in the order in which that subset fires. This is an interesting companion to several recent works in the neuroscience literature, showing that human memories may be stored in terms of neural spike timings. In our model, the ordering is stored in static synaptic weights using a Hebbian single-shot learning algorithm, and can be reliably recovered whenever the associated input is supplied. It is shown that the memory can operate using only unipolar binary connections throughout. The behavior of the memory under noisy input conditions is also investigated. It is shown that the memory is capable of improving the quality of the data that passes through it. That is, under appropriate conditions the output retrieved from the memory is less noisy than the input used to retrieve it. Thus, this memory architecture could be used as a component in a complex system with stable noise properties and, we argue, it can be implemented using spiking neurons.Index Terms-Associative memory, neural networks (NNs), rank-order codes, sparse distributed memory (SDM), spiking neurons.

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Section: A Representing a Rank-order Codementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Sparse Distributed Memory Using Rank-Order Neural Codes

Furber

Brown

Bose

et al. 2007

IEEE Trans. Neural Netw.

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“…Em psicologia, trabalhos como os baseados em Newell, Shaw e Simon (1965) constituem projetos de pesquisa relevantes que introduziram a simulação computacional utilizando representações. Uma representação constitui uma imagem, modelo ou reprodução que usualmente serve para aprimorar o entendimento do objeto representado (SUPPES;PAVEL;FALMAGNE, 1994).…”

Section: Introductionunclassified

Difusão de Inovações entre Consumidores Conectados em Redes Sociais

2011

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ResumoNo modelo computacional desenvolvido neste artigo, estuda-se a dinâmica de propagação de informações ou inovações, visando identificar como ideias, tecnologias ou produtos se difundem entre indivíduos dentro de uma rede social. Os resultados do modelo sugerem grande dependência da propagação de tecnologias às condições iniciais da população, refletidas pela distribuição da propensão inicial dos indivíduos em aceitarem uma nova ideia ou um novo produto. Quando há aversão da população à inovação, esforços devem ser focados em formadores de opinião, que induzirão outras pessoas a romperem barreiras para a adoção da ideia ou produto. Adicionalmente, devem ser privilegiadas estratégias de divulgação que façam as pessoas atribuírem peso maior, no seu processo decisório, a determinados estímulos que recebem. Neste contexto, o fato de um produto ou ideia estar na moda afeta a velocidade da

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“…Sparse distributed memory (SDM) [6] is an interesting form of associative memory, popular in both computer science and psychology [7]. It represents both an interesting storage device and plausible mathematical model of human long-term memory [6], [8], [9] that meets all above-mentioned demands.…”

Section: Introductionmentioning

confidence: 99%

Sparse distributed memory for experience-based robot manipulation

Jockel¹,

Lindner²,

Zhang³

2009

2008 IEEE International Conference on Robotics and Biomimetics

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Abstract-Sparse distributed memory (SDM) is a mathematical technique based on the properties of high-dimensional space for storing and retrieving large binary patterns. This model has been proposed for cerebellar functions, and has been used in simple visual and linguistic applications to date. This paper presents an SDM for robotic applications, especially for storing and recognising mobile manipulation actions of a 6-DOF robot arm. Sequences of events are stored as subjective experiences and are later used to guide robot arm behaviour based on its memory content. Several simple manipulation tasks, such as lift and place a wastebin from and on the floor, push an object aside on a tabletop, and draw shapes in the air are analysed under different operation modes. The robot system shows good reproduction abilities of task-dependent arm trajectories based on sparse distributed memory. Moreover, the content-addressable, associative memory even predicts the residual arm trajectory of a task if the arm is placed somewhere close to a learnt trajectory.

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Representations and Models in Psychology

Cited by 16 publications

References 23 publications

Sparse Distributed Memory Using Rank-Order Neural Codes

Sparse Distributed Memory Using Rank-Order Neural Codes

Difusão de Inovações entre Consumidores Conectados em Redes Sociais

Sparse distributed memory for experience-based robot manipulation

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