Retrieving of Remembrances via a Computational Cognitive Model of Knowledge Representation
نویسنده
چکیده
To understand oneself is one of the greatest challenges for man. Subsequently, a multitude of theories was proposed by the past to model the mind and the behaviour that it dictates. Nowadays, computational technology has progressed to the point that partial implementations of mental models can be rigorously constructed. ACT-R (Anderson et al., 2004) is a computational cognitive theory that allows modellers to develop simulations of human behaviour that cover a wild variety of cognitive phenomena. This implies that the popular ACT-R architecture can offers a fair approximation of human cognitive ability. However, some exceptions do not support this conventional wisdom.
منابع مشابه
A novel model of clinical reasoning: Cognitive zipper model
Introduction: Clinical reasoning is a vital aspect of physiciancompetence. It has been the subject of academic research fordecades, and various models of clinical reasoning have beenproposed. The aim of the present study was to develop a theoreticalmodel of clinical reasoning.Methods: To conduct our study, we applied the process of theorysynthesis in accordan...
متن کاملNeuron Mathematical Model Representation of Neural Tensor Network for RDF Knowledge Base Completion
In this paper, a state-of-the-art neuron mathematical model of neural tensor network (NTN) is proposed to RDF knowledge base completion problem. One of the difficulties with the parameter of the network is that representation of its neuron mathematical model is not possible. For this reason, a new representation of this network is suggested that solves this difficulty. In the representation, th...
متن کاملDeblocking Joint Photographic Experts Group Compressed Images via Self-learning Sparse Representation
JPEG is one of the most widely used image compression method, but it causes annoying blocking artifacts at low bit-rates. Sparse representation is an efficient technique which can solve many inverse problems in image processing applications such as denoising and deblocking. In this paper, a post-processing method is proposed for reducing JPEG blocking effects via sparse representation. In this ...
متن کاملComputationally Efficient Forgetting via Base-Level Activation
As we apply cognitive models to complex, temporally extended tasks, removing declarative knowledge from memory, or forgetting, will become important both to model human behavior, as well as to scale computationally. The base-level activation (BLA) model predicts that the availability of specific memories is sensitive to frequency and recency of use. Memory decay based on this model has long bee...
متن کاملImage Classification via Sparse Representation and Subspace Alignment
Image representation is a crucial problem in image processing where there exist many low-level representations of image, i.e., SIFT, HOG and so on. But there is a missing link across low-level and high-level semantic representations. In fact, traditional machine learning approaches, e.g., non-negative matrix factorization, sparse representation and principle component analysis are employed to d...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2006