It is well known that there exists a tight connection between nonmonotonic reasoning and conditional implication. Many researchers have investigated it from various angles. Among th em, C.Boutilier and P.Lamarre hav...It is well known that there exists a tight connection between nonmonotonic reasoning and conditional implication. Many researchers have investigated it from various angles. Among th em, C.Boutilier and P.Lamarre have shown that some conditional implication may b e regarded as the homology of different nonmonotonic consequence relations. In t his paper, based on the plausibility space introduced by Friedman and Halpern, w e characterize the condition logic in which conditional implication is nonmonoto nic, and this result characterizes the conditional implication which may be rega rded as the corresponding object in Meta language for nonmonotonic inference rel ations.展开更多
Based on the achievements of domestic and foreign scholars,the concept of the creativity support system(CSS)is introduced and two basic characteristics of the CSS are concluded:one is based on information technology,t...Based on the achievements of domestic and foreign scholars,the concept of the creativity support system(CSS)is introduced and two basic characteristics of the CSS are concluded:one is based on information technology,the other is assisting users in creatively solving problems.Then,the rationale as well as the correlative knowledge of the creativity support system is analyzed.Finally,according to the software that has been developed,the creativity support system's characteristics of the function is discussed.展开更多
This paper presents the differences and relations between background knowledge and domain theories in learning systems. The roles they play during learning procedures are discussed. It is emphasized that background k...This paper presents the differences and relations between background knowledge and domain theories in learning systems. The roles they play during learning procedures are discussed. It is emphasized that background knowledge plays an important role in enhancing the ability of a learning system. An explanation based learning system with domain theory in primary knowledge base and background knowledge in secondary knowledge base is introduced as an example. It shows how background knowledge can be used to solve some of the problems caused by incomplete domain theory in an explanation based learning system. The system can accomplish knowledge level learning through purely deductive approach. At last the acquisition of background knowledge is briefly discussed.展开更多
Immune evolutionary algorithms with domain knowledge were presented to solve the problem of simultaneous localization and mapping for a mobile robot in unknown environments. Two operators with domain knowledge were de...Immune evolutionary algorithms with domain knowledge were presented to solve the problem of simultaneous localization and mapping for a mobile robot in unknown environments. Two operators with domain knowledge were designed in algorithms, where the feature of parallel line segments without the problem of data association was used to construct a vaccination operator, and the characters of convex vertices in polygonal obstacle were extended to develop a pulling operator of key point grid. The experimental results of a real mobile robot show that the computational expensiveness of algorithms designed is less than other evolutionary algorithms for simultaneous localization and mapping and the maps obtained are very accurate. Because immune evolutionary algorithms with domain knowledge have some advantages, the convergence rate of designed algorithms is about 44% higher than those of other algorithms.展开更多
The expert system MUST (Mining Under Structures) shown in this paper and established by the authors is a preliminary expert system to solve the policy-making problems for mining under structures by means of computers ...The expert system MUST (Mining Under Structures) shown in this paper and established by the authors is a preliminary expert system to solve the policy-making problems for mining under structures by means of computers instead of humanbeing. Based on the experience of relative experts,the authors established a knowledge base about the minings under structures,researched into reasonable method to simulate thinking processes of human experts when they are solving the problems, established the network of an expert system and named it ' MUST system' . MUST system uses the method of the structural system analysis approach. A kind of methods of Turbo Prolog and Fortran 77 language alternations is designed to meet the needs of exchange information within the MUST system. Based on this kind of methods MUST system has been constructed and realised on IBM-PC computer. For verifying the correctness, suitability and reliablity of MUST system,some practical examples of minings under structures were tentatively solved using MUST system,whose results are satisfactory.展开更多
Updating or conditioning a body of evidence modeled within the DS framework plays an important role in most of Artificial Intelligence (AI) applications. Rule is one of the most important methods to represent knowledg...Updating or conditioning a body of evidence modeled within the DS framework plays an important role in most of Artificial Intelligence (AI) applications. Rule is one of the most important methods to represent knowledge in AI. The appearance of uncertain reasoning urges us to measure the belief of rule. Now,most of uncertain reasoning models represent the belief of rule by conditional probability. However,it has many limitations when standard conditional probability is used to measure the belief of expert system rule. In this paper,AI rule is modelled by conditional event and the belief of rule is measured by conditional event probability,then we use random conditional event to construct a new evidence updating method. It can overcome the drawback of the existed methods that the forms of focal sets influence updating result. Some examples are given to illustrate the effectiveness of the proposed method.展开更多
The paper presents an extension multi-laye r p erceptron model that is capable of representing and reasoning propositional know ledge base. An extended version of propositional calculus is developed, and its some prop...The paper presents an extension multi-laye r p erceptron model that is capable of representing and reasoning propositional know ledge base. An extended version of propositional calculus is developed, and its some properties is discussed. Formulas of the extended calculus can be expressed in the extension multi-layer perceptron. Naturally, semantic deduction of prop ositional knowledge base can be implement by the extension multi-layer perceptr on, and by learning, an unknown formula set can be found.展开更多
文摘It is well known that there exists a tight connection between nonmonotonic reasoning and conditional implication. Many researchers have investigated it from various angles. Among th em, C.Boutilier and P.Lamarre have shown that some conditional implication may b e regarded as the homology of different nonmonotonic consequence relations. In t his paper, based on the plausibility space introduced by Friedman and Halpern, w e characterize the condition logic in which conditional implication is nonmonoto nic, and this result characterizes the conditional implication which may be rega rded as the corresponding object in Meta language for nonmonotonic inference rel ations.
基金The National Key Technology R&D Program of China during the 11th Five-Year Plan Period(No.2006BAH02A06)
文摘Based on the achievements of domestic and foreign scholars,the concept of the creativity support system(CSS)is introduced and two basic characteristics of the CSS are concluded:one is based on information technology,the other is assisting users in creatively solving problems.Then,the rationale as well as the correlative knowledge of the creativity support system is analyzed.Finally,according to the software that has been developed,the creativity support system's characteristics of the function is discussed.
文摘This paper presents the differences and relations between background knowledge and domain theories in learning systems. The roles they play during learning procedures are discussed. It is emphasized that background knowledge plays an important role in enhancing the ability of a learning system. An explanation based learning system with domain theory in primary knowledge base and background knowledge in secondary knowledge base is introduced as an example. It shows how background knowledge can be used to solve some of the problems caused by incomplete domain theory in an explanation based learning system. The system can accomplish knowledge level learning through purely deductive approach. At last the acquisition of background knowledge is briefly discussed.
基金Projects(60234030 60404021) supported by the National Natural Science Foundation of China
文摘Immune evolutionary algorithms with domain knowledge were presented to solve the problem of simultaneous localization and mapping for a mobile robot in unknown environments. Two operators with domain knowledge were designed in algorithms, where the feature of parallel line segments without the problem of data association was used to construct a vaccination operator, and the characters of convex vertices in polygonal obstacle were extended to develop a pulling operator of key point grid. The experimental results of a real mobile robot show that the computational expensiveness of algorithms designed is less than other evolutionary algorithms for simultaneous localization and mapping and the maps obtained are very accurate. Because immune evolutionary algorithms with domain knowledge have some advantages, the convergence rate of designed algorithms is about 44% higher than those of other algorithms.
文摘The expert system MUST (Mining Under Structures) shown in this paper and established by the authors is a preliminary expert system to solve the policy-making problems for mining under structures by means of computers instead of humanbeing. Based on the experience of relative experts,the authors established a knowledge base about the minings under structures,researched into reasonable method to simulate thinking processes of human experts when they are solving the problems, established the network of an expert system and named it ' MUST system' . MUST system uses the method of the structural system analysis approach. A kind of methods of Turbo Prolog and Fortran 77 language alternations is designed to meet the needs of exchange information within the MUST system. Based on this kind of methods MUST system has been constructed and realised on IBM-PC computer. For verifying the correctness, suitability and reliablity of MUST system,some practical examples of minings under structures were tentatively solved using MUST system,whose results are satisfactory.
基金Supported by the NSFC (No. 60772006, 60874105)the ZJNSF (Y1080422, R106745)Aviation Science Foundation (20070511001)
文摘Updating or conditioning a body of evidence modeled within the DS framework plays an important role in most of Artificial Intelligence (AI) applications. Rule is one of the most important methods to represent knowledge in AI. The appearance of uncertain reasoning urges us to measure the belief of rule. Now,most of uncertain reasoning models represent the belief of rule by conditional probability. However,it has many limitations when standard conditional probability is used to measure the belief of expert system rule. In this paper,AI rule is modelled by conditional event and the belief of rule is measured by conditional event probability,then we use random conditional event to construct a new evidence updating method. It can overcome the drawback of the existed methods that the forms of focal sets influence updating result. Some examples are given to illustrate the effectiveness of the proposed method.
文摘The paper presents an extension multi-laye r p erceptron model that is capable of representing and reasoning propositional know ledge base. An extended version of propositional calculus is developed, and its some properties is discussed. Formulas of the extended calculus can be expressed in the extension multi-layer perceptron. Naturally, semantic deduction of prop ositional knowledge base can be implement by the extension multi-layer perceptr on, and by learning, an unknown formula set can be found.
