R. Dechter, , and A. Dechter, , Structure driven algorithms for truth maintenance, Artificial Intelligence Journal, 82, pp. 1-20, 1996.  Home/Search   Document Details and Download   Summary   Related Articles   Check

.... is that it makes it possible to obtain generic structural results concerning the computational complexity of constraint satisfaction problems that can be applied in many di erent areas such as database theory [27] temporal and spatial reasoning [25] machine vision [17] belief maintenance [7], technical design [18] natural language comprehension [1] and programming language analysis [19] The general constraint satisfaction problem is NP complete. There are two main streams in the study of this problem: the search for heuristics (see e.g. 6, 16] and the investigation of how ....

Dechter R., Dechter A., Structure-driven algorithms for truth maintenance, Arti- cial Intelligence, 82(1-2), 1996, 1-20.

....of problem structure in automated reasoning has become a major computational technique in certain communities and is gaining momentum in others. In probabilistic reasoning and constraint satisfaction, structure is the main aspect of a problem which is used to control the complexity of inference [ Dechter and Dechter, 1996; Jensen et al. 1990; Pearl, 1988 ] In probabilistic reasoning, structure refers to the topology of a Bayesian network, and in constraint satisfaction it refers to the topology of a constraint network. Structurebased reasoning has also been introduced to modelbased diagnosis, where structure ....

....refers to the topology of a Bayesian network, and in constraint satisfaction it refers to the topology of a constraint network. Structurebased reasoning has also been introduced to modelbased diagnosis, where structure refers to the interconnectivity of device components [ Hamscher et al. 1992; Dechter and Dechter, 1996; Geffner and Pearl, 1987; Darwiche, 1998 ] One of the most interesting aspects of structure based diagnosis is that it ties the complexity of computing diagnoses to a very intuitive measure: component interconnectivity. As it turns out, the less connected a device is, the easier it is to ....

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Rina Dechter and Avi Dechter. Structure-driven algorithms for truth maintenance. Artificial Intelligence, 82:1--20, 1996.

....as the key components. By using this paradigm, one is guaranteed some complexity results that are parameterized by the topology of the system s causal structure. As we shall see, this approach is based on the causal network paradigm in the probabilistic and constraint satisfaction literatures [ Dechter and Dechter, 1994; Geffner and Pearl, 1987; Dechter and Dechter, 1988 ] In both cases, the system F B C E A D D X B C A F E Y Z (D or E) and ok(Z) implies F not (D or E) and ok(Z) implies not F B and C and ok(Y) implies E not (B and C) and ok(Y) implies notE A and ok(X) implies not D not A and ok(X) implies D ....

....diagnostic practitioners with more flexibility in engineering the response time of their applications. This emphasis on structure has been the central theme in probabilistic reasoning lately [ Pearl, 1988 ] There have been some several attempts to import this theme into model based diagnosis [ Dechter and Dechter, 1994; Geffner and Pearl, 1987; Dechter and Dechter, 1988 ] A number of structurebased algorithms have been provided for computing the most likely diagnoses, which seem to have similar computational complexity and appeal to the same underlying principles. Previous algorithms, however, have rested on ....

Rina Dechter and Avi Dechter. Structure-driven algorithms for truth maintenance. Artificial Intelligence, 1994. To appear.

....for programs that are close to being stratified. Several tractable subclasses for computing extensions of default theories (and, hence, computing stable models) are known (Kautz Selman, 1991; Papadimitriou Sideri, 1994; Palopoli Zaniolo, 1996; Dimopoulos Magirou, 1994; Ben Eliyahu Dechter, 1996). Some of these tractable subclasses are characterized using a graph that reflects dependencies in the program between atoms and rules. The algorithms presented in these papers are complete only for a subclass of all knowledge bases, however. Algorithms for computing extensions of stratified ....

Dechter, R., & Dechter, A. (1996). Structure-driven algorithms for truth maintenance.

....to the network paradigm in the probabilistic and constraint satisfaction literature where system structure is the key aspect that decides the difficulty of a reasoning problem. The literature contains a number of other proposals for importing this structure based theme into model based diagnosis (Dechter Dechter, 1996; Geffner Pearl, 1987) Although these approaches appeal to similar underlying principles and lead to similar complexity results, some key differences exist between our approach and the previous ones. First, our formulation is based on symbolic logic, which is the tradition in model based ....

....it provides diagnostic practitioners with more flexibility in engineering the response time of their applications. This emphasis on structure has been the central theme in probabilistic reasoning lately and there are a number of other algorithms for importing this theme into model based diagnosis (Dechter Dechter, 1996; Geffner Pearl, 1987) There are some key differences, however, between our proposal and the previous ones: Given consequences and the theorems to manipulate them, our proposal can be viewed as a framework for structure based diagnosis instead of simply an algorithm. We did propose a specific ....

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Dechter, R., & Dechter, A. (1996). Structure-driven algorithms for truth maintenance.

....This leads to a computational paradigm in which the complexity of reasoning is parameterized by the topology of a database structure. This structure based approach is at the heart of causal networks in the probabilistic literature and constraint networks in the constraint satisfaction literature [9, 12, 8]. In both cases, a graphical structure is the key aspect deciding the difficulty of a reasoning problem. This structure is what users need to control in order to ensure an appropriate response time for their applications. The probabilistic literature, for example, contains techniques for tweaking ....

Rina Dechter and Avi Dechter. Structure-driven algorithms for truth maintenance. Artificial Intelligence, 1994. To appear.

.... structure into a join tree; the consequence is exponential in the size of the biggest clique in that tree [5] The literatures on constraint satisfaction and probabilistic reasoning contain many results on the connection between topology and computational complexity relevant to this approach [11, 15, 10]. Structured system descriptions and consequences have been used quite successfully on a number of domains that involve the diagnosis of space shuttle controllers and avionics systems of commercial airplanes (details of these applications are beyond the scope of this document) This success is a ....

Rina Dechter and Avi Dechter. Structure-driven algorithms for truth maintenance. Artificial Intelligence, 1994. To appear.

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A. Dechter and R. Dechter. Structure-driven algorithms for truth maintenance. Artificial Intelligence, 1985.

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R. Dechter, , and A. Dechter, , Structure driven algorithms for truth maintenance, Artificial Intelligence Journal, 82, pp. 1-20, 1996.

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Intelligence 28:127--162. Dechter, R., and Dechter, A. 1996. Structure-driven algorithms for truth maintenance. Artificial Intelligence 82:1--20.

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