標(biāo)題: Titlebook: Deep Fusion of Computational and Symbolic Processing; Takeshi Furuhashi,Shun’Ichi Tano,Hans-Arno Jacobse Book 2001 Springer-Verlag Berlin [打印本頁] 作者: 驅(qū)逐 時間: 2025-3-21 17:34
書目名稱Deep Fusion of Computational and Symbolic Processing影響因子(影響力)
書目名稱Deep Fusion of Computational and Symbolic Processing影響因子(影響力)學(xué)科排名
書目名稱Deep Fusion of Computational and Symbolic Processing網(wǎng)絡(luò)公開度
書目名稱Deep Fusion of Computational and Symbolic Processing網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Deep Fusion of Computational and Symbolic Processing被引頻次
書目名稱Deep Fusion of Computational and Symbolic Processing被引頻次學(xué)科排名
書目名稱Deep Fusion of Computational and Symbolic Processing年度引用
書目名稱Deep Fusion of Computational and Symbolic Processing年度引用學(xué)科排名
書目名稱Deep Fusion of Computational and Symbolic Processing讀者反饋
書目名稱Deep Fusion of Computational and Symbolic Processing讀者反饋學(xué)科排名
作者: ANTI 時間: 2025-3-21 22:10
978-3-662-00373-2Springer-Verlag Berlin Heidelberg 2001作者: 獎牌 時間: 2025-3-22 00:42
https://doi.org/10.1007/978-1-4842-3603-1st (symbolic) and distributed representations, based on the two-level approach proposed in Sun (1995). The model learns and utilizes procedural and declarative knowledge, tapping into the synergy of the two types of processes. It unifies neural, reinforcement, and symbolic methods to perform on-line作者: 推遲 時間: 2025-3-22 06:42
https://doi.org/10.1007/978-1-4842-3603-1se methods is studied. A special processor to combine different methods is necessary for integration. It is called an integrator. Among various information-processing methods, only declarative knowledge-based method is suited for an integrator. Then the realistic way of developing the integrator is 作者: 我要沮喪 時間: 2025-3-22 09:42 作者: Ablation 時間: 2025-3-22 16:30 作者: Ablation 時間: 2025-3-22 17:09
https://doi.org/10.1007/978-1-4842-3603-1 “fuzzy” sequential knowledge for the description of dynamic characteristics of a system. Symbolic Dynamic System(SDS), a model for symbolic sequences, is extended to deal with “fuzzy” symbolic sequences. This approach introduces topological nature into the symbolic sequences, which allows an interp作者: 無畏 時間: 2025-3-23 00:51
https://doi.org/10.1007/978-1-4842-3603-1 comparison with its predecessor because the learning and the knowledge extraction process are faster and are accomplished in an incremental way . INSS offers a new approach applicable to constructive machine learning with high-performance tools, even in the presence of incomplete or erroneous data.作者: freight 時間: 2025-3-23 01:33 作者: dissent 時間: 2025-3-23 05:46 作者: CURB 時間: 2025-3-23 12:33
Design Patterns in Modern C++20ovide a strong notation connecting the symbolic representation to the real world. In this paper, we discuss Conceptual Fuzzy Sets (CFS), a new type of fuzzy sets which conform to Wittgenstein’s ideas.. In CFS the meaning of a concept is represented by the distribution of activation of labels in asso作者: HOWL 時間: 2025-3-23 16:51 作者: Shuttle 時間: 2025-3-23 21:06 作者: 在前面 時間: 2025-3-24 01:36
Deep Fusion of Computational and Symbolic Processing978-3-7908-1837-6Series ISSN 1434-9922 Series E-ISSN 1860-0808 作者: 臭名昭著 時間: 2025-3-24 03:58 作者: Bereavement 時間: 2025-3-24 08:53
Takeshi Furuhashi,Shun’Ichi Tano,Hans-Arno JacobseFirst publication of recent results of study under the name of integration of computational processing and symbolic processing.Thorough coverage of recent attempts to combine/hybridize/fuse symbolic p作者: innovation 時間: 2025-3-24 12:14
Studies in Fuzziness and Soft Computinghttp://image.papertrans.cn/d/image/264552.jpg作者: 表示向下 時間: 2025-3-24 18:54 作者: Forsake 時間: 2025-3-24 22:49 作者: 關(guān)節(jié)炎 時間: 2025-3-25 01:13
https://doi.org/10.1007/978-1-4842-3603-1, bottom-up learning (from subsymbolic to symbolic knowledge). Experiments in various situations shed light on the working of the model. Its theoretical implications in terms of symbol grounding are also discussed.作者: 精密 時間: 2025-3-25 05:01 作者: lambaste 時間: 2025-3-25 08:08
Book 2001 and fuse these processing methods should be thoroughly investigated and the direction of novel fusion approaches should be clarified. This book contains the current status of this attempt and also discusses future directions.作者: ARC 時間: 2025-3-25 15:27 作者: emulsify 時間: 2025-3-25 17:59
https://doi.org/10.1007/978-1-4842-7295-4ich an upper level concept includes the lower level concepts. The neural network implementing the concept of the AR consists of Kohonen feature maps and it employs a new learning algorithm named neighborhood Hebbian learning. Each map is connected and forms multidirectional associative memory.作者: 存心 時間: 2025-3-25 22:17
New Paradigm toward Deep Fusion of Computational and Symbolic Processing propose a new paradigm toward deep fusion of computational and symbolic processing and show the new model as the first step of the paradigm. The model is realized by “Symbol Emergence Method for Q-Learning Neural Network”. We testified the validity of the new method.作者: 反應(yīng) 時間: 2025-3-26 00:12 作者: Sigmoidoscopy 時間: 2025-3-26 05:43 作者: 好開玩笑 時間: 2025-3-26 09:23 作者: 琺瑯 時間: 2025-3-26 13:18
Symbol Pattern Integration Using Multilinear Functionsear function space, which is an extension of Boolean algebra of Boolean functions and basically includes neural networks. The space is an algebraic model of several nonclassical logics. The above two integrations can be realized by the multilinear function space.作者: 慢慢流出 時間: 2025-3-26 20:11
https://doi.org/10.1007/978-1-4842-3603-1c methods of information processing. The difference between symbolic and non-symbolic methods is clarified by representing them by the same mathematical formula and based on this result a possible extension of knowledge-based processing is proposed in order to expand the scope of integration.作者: overhaul 時間: 2025-3-27 00:42 作者: 同位素 時間: 2025-3-27 03:24 作者: Scintigraphy 時間: 2025-3-27 06:18
Design Patterns in Modern C++20ing of the same concept as it is used in various expressions in each layer. As the propagation of activations corresponds to reasoning, multi-layered reasoning in CFS has following features; 1) capable of simultaneous top-down and bottom-up processing, 2) capable of context sensitive knowledge processing.作者: paltry 時間: 2025-3-27 11:40
Integration of Different Information Processing Methodsc methods of information processing. The difference between symbolic and non-symbolic methods is clarified by representing them by the same mathematical formula and based on this result a possible extension of knowledge-based processing is proposed in order to expand the scope of integration.作者: bonnet 時間: 2025-3-27 16:10
Design of Autonomously Learning Controllers Using ,cy as, for example, a fuzzy or linear control law considerably improves the learning process. Moreover, the learned policy can be interpreted as fuzzy control law which allows for easily checking the plausibility.作者: 領(lǐng)導(dǎo)權(quán) 時間: 2025-3-27 21:13 作者: Lymphocyte 時間: 2025-3-28 01:37 作者: nuclear-tests 時間: 2025-3-28 02:41 作者: Anticoagulants 時間: 2025-3-28 07:00
https://doi.org/10.1007/978-1-4842-7295-4at is one of self-organizing network method. This method is constructing an incremental network structure given an input sequence. We applied this method to gesture motion images, so that we extract common parts in some gestures and singular parts. We show detail of incremental path method in sectio作者: Incorporate 時間: 2025-3-28 10:39
Deep Fusion of Computational and Symbolic Processing作者: 大約冬季 時間: 2025-3-28 16:59
A Generic Architecture for Hybrid Intelligent Systems a unifying paradigm, well known in the artificial intelligence community. This paradigm serves us as conceptual framework to better understand, modularize, compare, and evaluate the individual approaches. We think it is crucial for the design of intelligent systems to focus on the integration and i作者: Autobiography 時間: 2025-3-28 22:24 作者: 不知疲倦 時間: 2025-3-29 00:12 作者: vascular 時間: 2025-3-29 06:01 作者: Irritate 時間: 2025-3-29 10:52
Integration of Different Information Processing Methodsse methods is studied. A special processor to combine different methods is necessary for integration. It is called an integrator. Among various information-processing methods, only declarative knowledge-based method is suited for an integrator. Then the realistic way of developing the integrator is 作者: facetious 時間: 2025-3-29 15:05
Symbol Pattern Integration Using Multilinear Functions with by logical reasoning. The typical pattern processing is neural networks, where patterns are dealt with by numerical computation. The integration of symbols and patterns means numerical computation of symbols and logical reasoning of patterns, that is, pattern reasoning. The key is the multilin作者: Fortuitous 時間: 2025-3-29 17:07
Design of Autonomously Learning Controllers Using ,rement: without knowledge of a process model the system learns a control policy. Optimization goals like time-optimal or energy-optimal control as well as restrictions of allowed manipulated variables or system states can be defined in a simple and flexible way. . only learns on basis of success and作者: TEM 時間: 2025-3-29 19:55
Modeling for Dynamic Systems with Fuzzy Sequential Knowledge “fuzzy” sequential knowledge for the description of dynamic characteristics of a system. Symbolic Dynamic System(SDS), a model for symbolic sequences, is extended to deal with “fuzzy” symbolic sequences. This approach introduces topological nature into the symbolic sequences, which allows an interp作者: 大猩猩 時間: 2025-3-30 02:14
Hybrid Machine Learning Tools: INSS — A Neuro-Symbolic System for Constructive Machine Learning comparison with its predecessor because the learning and the knowledge extraction process are faster and are accomplished in an incremental way . INSS offers a new approach applicable to constructive machine learning with high-performance tools, even in the presence of incomplete or erroneous data.作者: 無王時期, 時間: 2025-3-30 06:06
A Generic Architecture for Hybrid Intelligent Systemshrough hybridization or fusion, has in recent years contributed to a large number of new intelligent system designs. Many of these approaches, however, follow an ad hoc design methodology, further justified by success in certain application domains. Due to the lack of a common framework it remains o
