標(biāo)題: Titlebook: Computational Architectures Integrating Neural and Symbolic Processes; A Perspective on the Ron Sun,Lawrence A. Bookman Book 1995 Springer [打印本頁(yè)] 作者: fasten 時(shí)間: 2025-3-21 17:58
書(shū)目名稱Computational Architectures Integrating Neural and Symbolic Processes影響因子(影響力)
書(shū)目名稱Computational Architectures Integrating Neural and Symbolic Processes影響因子(影響力)學(xué)科排名
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書(shū)目名稱Computational Architectures Integrating Neural and Symbolic Processes網(wǎng)絡(luò)公開(kāi)度學(xué)科排名
書(shū)目名稱Computational Architectures Integrating Neural and Symbolic Processes被引頻次
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書(shū)目名稱Computational Architectures Integrating Neural and Symbolic Processes年度引用
書(shū)目名稱Computational Architectures Integrating Neural and Symbolic Processes年度引用學(xué)科排名
書(shū)目名稱Computational Architectures Integrating Neural and Symbolic Processes讀者反饋
書(shū)目名稱Computational Architectures Integrating Neural and Symbolic Processes讀者反饋學(xué)科排名
作者: Blazon 時(shí)間: 2025-3-21 21:20 作者: stress-response 時(shí)間: 2025-3-22 00:28 作者: mutineer 時(shí)間: 2025-3-22 04:42
Subsymbolic Parsing of Embedded Structures systems have been quite successful, for example, in modeling in-depth natural language processing [., ., .], episodic memory [., ., and problem solving [., ., .]. In such systems, knowledge is encoded in terms of explicit symbolic structures, and processing is based on handcrafted rules that operat作者: 完成 時(shí)間: 2025-3-22 12:06 作者: cartilage 時(shí)間: 2025-3-22 13:37
An Internal Report for Connectionists has been concerned with the idea of distributed representations. Dissatisfied with the Symbolic tradition, and in search of the new, many cognitive theorists began to infiltrate connectionism in search of a new theory of mind. Like the Classicists, these theorists required that a constructed, analy作者: cartilage 時(shí)間: 2025-3-22 20:45
A Two-Level Hybrid Architecture for Structuring Knowledge for Commonsense Reasoningms of representation, and it consists of two levels: one is an inference network with nodes representing concepts and links representing rules connecting concepts, and the other is a microfeature-based replica of the first level. Based on the interaction between the concept nodes and microfeature no作者: Oration 時(shí)間: 2025-3-23 01:06
A Framework for Integrating Relational and Associational Knowledge for Comprehensione ability to read it “deeply” (a fine-grain view of comprehension). A computational analogue that mimics skimming should include a representation of a set of semantic relationships about the text that can be used to summarize it and extract what is important. A computational analogue that supports a作者: 多骨 時(shí)間: 2025-3-23 03:13
Examining a Hybrid Connectionist/Symbolic System for the Analysis of Ballistic SignalsI and connectionism. Some researchers .. have argued that symbolism and connectionism represent differing computational paradigms, while others have discussed merging the differing strengths and weaknesses of these approaches, as evidenced by the papers in this volume. The general consensus to date 作者: 易改變 時(shí)間: 2025-3-23 06:25
Symbolic Artificial Intelligence and Numeric Artificial Neural Networks: Towards a Resolution of the writings of India and Greece, this has been a central problem in philosophy. The advent of the digital computer in the 1950’s made this a central concern of computer scientists as well (.). The parallel development of the theory of computation (by John von Neumann, Alan Turing, EmilPost, Alonzo Chu作者: 不知疲倦 時(shí)間: 2025-3-23 10:13 作者: 脆弱帶來(lái) 時(shí)間: 2025-3-23 17:53 作者: 大喘氣 時(shí)間: 2025-3-23 21:50
https://doi.org/10.1007/978-3-642-84845-2 cell organisms to invertebrates, to vertebrates, and to humans, the truly intelligent beings. The biological organizations of various species, from the lowest to the highest, differ in their complexities and sizes. Such differences in internal complexity manifest in the differences in overt behavio作者: 生銹 時(shí)間: 2025-3-24 00:11
Studies in Systems, Decision and Controlsition Encoding (RPE) and . (PSA). The present article shows that the primitives are powerful and convenient for effecting cognitively sophisticated connectionist symbol processing. Specifically, it shows how RPE and PSA are used in a connectionist implementation of Johnson-Laird’s mental model theo作者: Congeal 時(shí)間: 2025-3-24 03:33 作者: Bureaucracy 時(shí)間: 2025-3-24 07:38
https://doi.org/10.1007/978-3-662-45623-1 systems have been quite successful, for example, in modeling in-depth natural language processing [., ., .], episodic memory [., ., and problem solving [., ., .]. In such systems, knowledge is encoded in terms of explicit symbolic structures, and processing is based on handcrafted rules that operat作者: CHOKE 時(shí)間: 2025-3-24 14:16 作者: 嚴(yán)重傷害 時(shí)間: 2025-3-24 16:01 作者: 盤旋 時(shí)間: 2025-3-24 21:23
https://doi.org/10.1007/978-3-7091-2969-2ms of representation, and it consists of two levels: one is an inference network with nodes representing concepts and links representing rules connecting concepts, and the other is a microfeature-based replica of the first level. Based on the interaction between the concept nodes and microfeature no作者: flimsy 時(shí)間: 2025-3-25 02:05
https://doi.org/10.1007/978-3-7091-2969-2e ability to read it “deeply” (a fine-grain view of comprehension). A computational analogue that mimics skimming should include a representation of a set of semantic relationships about the text that can be used to summarize it and extract what is important. A computational analogue that supports a作者: 持久 時(shí)間: 2025-3-25 06:06
N. V. Banichuk,Pekka Neittaanm?kiI and connectionism. Some researchers .. have argued that symbolism and connectionism represent differing computational paradigms, while others have discussed merging the differing strengths and weaknesses of these approaches, as evidenced by the papers in this volume. The general consensus to date 作者: 思鄉(xiāng)病 時(shí)間: 2025-3-25 08:59 作者: 高談闊論 時(shí)間: 2025-3-25 12:04
N. V. Banichuk,Pekka Neittaanm?kiative retrieval of memories. The summation and thresholding of activation allows for smooth integration of multiple sources of knowledge. CNs with distributed representations (.) exhibit robustness in the face of noise/damage and can learn to perform complex mapping tasks just from examples. Connect作者: 1FAWN 時(shí)間: 2025-3-25 16:17 作者: Relinquish 時(shí)間: 2025-3-25 20:57
Hierarchical Architectures for ReasoningThis chapter has a threefold purpose: (1) to introduce a general framework for parallel/distributed computation, the .; (2) to expose in detail a symbolic example of a computational network, related to expert systems, called an .; and (3) to describe and investigate how an expert network can be realized as a neural network possessing a ..作者: 吹牛者 時(shí)間: 2025-3-26 00:56
Subsymbolic Parsing of Embedded Structures systems have been quite successful, for example, in modeling in-depth natural language processing [., ., .], episodic memory [., ., and problem solving [., ., .]. In such systems, knowledge is encoded in terms of explicit symbolic structures, and processing is based on handcrafted rules that operate on these structures.作者: 啤酒 時(shí)間: 2025-3-26 06:07
https://doi.org/10.1007/b102608Processing; artificial intelligence; cognitive psychology; cognitive science; computer; computer science; 作者: finite 時(shí)間: 2025-3-26 12:17
978-1-4757-8319-3Springer Science+Business Media New York 1995作者: paleolithic 時(shí)間: 2025-3-26 13:14 作者: Omnipotent 時(shí)間: 2025-3-26 18:03 作者: 致詞 時(shí)間: 2025-3-26 20:58 作者: 或者發(fā)神韻 時(shí)間: 2025-3-27 04:08
Book 1995 research. With the reemergence of neuralnetworks in the 1980s with their emphasis on overcoming some of thelimitations of symbolic AI, there is clearly a need to support someform of high-level symbolic processing in connectionist networks. Asargued by many researchers, on both the symbolic AI and c作者: 嚙齒動(dòng)物 時(shí)間: 2025-3-27 05:31 作者: 使顯得不重要 時(shí)間: 2025-3-27 13:08
A Two-Level Hybrid Architecture for Structuring Knowledge for Commonsense Reasoningdes in the architecture, inferences are facilitated and knowledge not explicitly encoded in a system can be deduced via a mixture of similarity matching and rule application. The architecture is able to take account of many important desiderata of plausible commonsense reasoning, and produces sensible conclusions.作者: Diuretic 時(shí)間: 2025-3-27 17:30
A Framework for Integrating Relational and Associational Knowledge for Comprehension deep reading of the text should be able to represent the background details (nonsystematic relationships) associated with the concepts in the text, including the larger frame in which the text concepts are situated.作者: 窩轉(zhuǎn)脊椎動(dòng)物 時(shí)間: 2025-3-27 19:32
Connectionist Natural Language Processing: A Status Reportionist networks are also able to dynamically reinterpret situations as new inputs are received. These features are very useful for natural language processing (NLP) and offer the hope that connectionist approaches to NLP will replace the more traditional, symbolic approaches to NLP.作者: 小畫(huà)像 時(shí)間: 2025-3-27 23:16 作者: BLAZE 時(shí)間: 2025-3-28 05:22 作者: 憲法沒(méi)有 時(shí)間: 2025-3-28 08:29 作者: 丑惡 時(shí)間: 2025-3-28 11:24 作者: CLAN 時(shí)間: 2025-3-28 14:37
Studies in Systems, Decision and Control exact, Conposit is a general framework for implementing rule-based systems in connectionism, and Conposit/SYLL is just one instance of it. (The name “Conposit” is derived from “Connectionist POSI-Tional encoding.” Conposit/SYLL is a major extension beyond the preliminary version described in .).作者: 濃縮 時(shí)間: 2025-3-28 21:14
Complex Symbol-Processing in Conposit, A Transiently Localist Connectionist Architecture exact, Conposit is a general framework for implementing rule-based systems in connectionism, and Conposit/SYLL is just one instance of it. (The name “Conposit” is derived from “Connectionist POSI-Tional encoding.” Conposit/SYLL is a major extension beyond the preliminary version described in .).作者: 未開(kāi)化 時(shí)間: 2025-3-29 00:50
N. V. Banichuk,Pekka Neittaanm?kien used more successfully in pattern recognition and other perceptual tasks. Interestingly enough, the strengths of symbolic systems correspond to the weaknesses of connectionist systems and vice versa.作者: 制定 時(shí)間: 2025-3-29 06:06
N. V. Banichuk,Pekka Neittaanm?kicomputers and programs that exhibit aspects of intelligent behavior — such as the ability to recognize and classify patterns; to reason from premises to logical conclusions; and to learn from experience.作者: MAIZE 時(shí)間: 2025-3-29 07:26
Examining a Hybrid Connectionist/Symbolic System for the Analysis of Ballistic Signalsen used more successfully in pattern recognition and other perceptual tasks. Interestingly enough, the strengths of symbolic systems correspond to the weaknesses of connectionist systems and vice versa.作者: Fester 時(shí)間: 2025-3-29 14:49 作者: 舊石器 時(shí)間: 2025-3-29 15:44
An Introduction: On Symbolic Processing in Neural Networkstive difference. Yet, strange enough, there is no known qualitative difference between the biological make-up of human brains and animal brains. So the questions are: Where does the difference lie? What is the key to the emergence of rational thinking and intelligence?作者: Visual-Field 時(shí)間: 2025-3-29 20:42
Towards Instructable Connectionist Systemstwo channels for the bulk of their knowledge acquisition. Specifically, symbolic artificial intelligence systems have generally depended upon the explicit use of sentential logical expressions, rules, or productions for the transmission of new knowledge to the system. In contrast, many connectionist作者: ARC 時(shí)間: 2025-3-30 00:57
An Internal Report for Connectionistsy virtue of the fact that they are similar to Classically conceived symbolic representations. For example, the structure of complex expression may be maintained in vector frames consisting of explicit tokens or complex expressions that are essentially passed around a net .. Only distributed represen作者: Ptsd429 時(shí)間: 2025-3-30 07:59
