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1.
Perceiving and Reasoning about a Changing World   总被引:1,自引:0,他引:1  
A rational agent (artificial or otherwise) residing in a complex changing environment must gather information perceptually, update that information as the world changes, and combine that information with causal information to reason about the changing world. Using the system of defeasible reasoning that is incorporated into the OSCAR architecture for rational agents, a set of reason‐schemas is proposed for enabling an agent to perform some of the requisite reasoning. Along the way, solutions are proposed for the Frame Problem, the Qualification Problem, and the Ramification Problem. The principles and reasoning described have all been implemented in OSCAR.  相似文献   

2.
基于智能体的混合知识自适应推理控制   总被引:2,自引:0,他引:2  
本文将传统的混合知识表示法推广,建立了一个将一般知识、案例知识、模型知识、模型知识及神经网络知识有机集成的结构.该种知识表示结构有助于知识的搜索、匹配和推理控制,解决了复杂问题的知识表示.为适应推理方法的需要,将各种不同的推理方法有机融合与集成,提出一种基于智能体的自适应推理控制结构,该种自适应推理控制结构对于改进解决复杂问题的效果以及提高解决复杂问题的效率具有重要意义。  相似文献   

3.
Abstract

The enterprise is the construction of a general theory of rationality, and its implementation in an automated reasoning system named OSCAR. The paper describes a general architecture for rational thought. This includes both theoretical reasoning and practical reasoning, and builds in important interconnections between them. It is urged that a sophisticated reasoner must be an introspective reasoner, capable of monitoring its own reasoning and reasoning about it. An introspective reasoner is built on top of a non-introspective reasoner that represents the system's default reasoning strategies. The introspective reasoner engages in practical reasoning about reasoning in order to override these default strategies. The paper concludes with a discussion of some aspects of the default reasoner, including the manner in which reasoning is interest driven, and the structure of defeasible reasoning.  相似文献   

4.
In this paper we discuss reasoning about reasoning in a multiple agent scenario. We consider agents that are perfect reasoners, loyal, and that can take advantage of both the knowledge and ignorance of other agents. The knowledge representation formalism we use is (full) first order predicate calculus, where different agents are represented by different theories, and reasoning about reasoning is realized via a meta-level representation of knowledge and reasoning. The framework we provide is pretty general: we illustrate it by showing a machine checked solution to the three wisemen puzzle. The agents' knowledge is organized into units: the agent's own knowledge about the world and its knowledge about other agents are units containing object-level knowledge; a unit containing meta-level knowledge embodies the reasoning about reasoning and realizes the link among units. In the paper we illustrate the meta-level architecture we propose for problem solving in a multi-agent scenario; we discuss our approach in relation to the modal one and we compare it with other meta-level architectures based on logic. Finally, we look at a class of applications that can be effectively modeled by exploiting the meta-level approach to reasoning about knowledge and reasoning.  相似文献   

5.
Knowledge-based computing, in general, suffers from an inherent open-endedness that precludes its application in time-bounded domains where an answer must be computed within a stipulated time limit. We examine a two-way improvement of the shortcomings: a knowledge representation scheme that provides easy access to relevant knowledge and thereby reduces search time, and a reasoning scheme that is algorithmic in nature and thus makes computational requirements meaningfully estimable.In this work, we offer a cache-based architecture that is capable of both storing knowledge in different formats (e.g. rules, cases), and invoking an appropriate reasoning scheme to fit the available computing time. The cache helps in retrieving the most relevant pieces of knowledge (not only exact matches) required for solving a given problem. This cache relies on a reasoning tactic, knowledge interpolation, that can generate a solution from two near-matches in an algorithmic way, to generate time-bounded solutions. We illustrate the design of such a cache for solving resource allocation problems in the domain of shortwave radio transmission and evaluate its performance in observing imposed temporal bounds.  相似文献   

6.
Among the non-monotonic reasoning processes, abduction is one of the most important. Usually described as the process of looking for explanations, it has been recognized as one of the most commonly used in our daily activities. Still, the traditional definitions of an abductive problem and an abductive solution mention only theories and formulas, leaving agency out of the picture. Our work proposes a study of abductive reasoning from an epistemic and dynamic perspective. In the first part we explore syntactic definitions of both an abductive problem in terms of an agent’s information and an abductive solution in terms of the actions that modify the agent’s information. We look at diverse kinds of agents, including not only omniscient ones but also those whose information is not closed under logical consequence and those whose reasoning abilities are not complete. In the second part, we look at an existing logical framework whose semantic model allows us to interpret the previously stated formulas, and we define two actions that represent forms of abductive reasoning.  相似文献   

7.
Audiences in argumentation frameworks   总被引:1,自引:0,他引:1  
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8.
9.
Abstract

Most of the expert systems applied in vegetal pathology treat the problem of selecting treatment in a conventional manner, by means of production rules that associate to each pathology the most adequate chemical product. This makes it difficult to generate useful explanations. In order to generate satisfactory explanations the knowledge of the system must be based on the strategies used by human experts. This article introduces our approach for the identification and representation of strategic knowledge in an expert system for plague control in greenhouses. We present an introduction to the application domain and make an analysis of the strategic knowledge implied. We distinguish between the underlying strategy and the practical strategy used by the expert for the solution of the problem. From this we propose a preliminary architecture based on strategic reasoning agents.  相似文献   

10.
In this paper, PRIMES (Progressive Reasoning and Intelligent multiple MEthods System), a new architecture for resource-bounded reasoning that combines a form of progressive reasoning and the so-called multiple methods approach is presented. Each time-critical reasoning unit is designed in such a way that it delivers an approximate result in time whenever an overload or a failure prevents the system from producing the most accurate result. Indeed, reasoning units use approximate processing based on two salient features. First, an incremental processing unit constructs an approximate solution quickly and then refines it incrementally. Second, a multiple methods approach proposes different alternatives to solve the problem, each of them being selected according to the available resources. In allowing several resource-bounded reasoning paradigms to be combined, we hope to extend their actual scope to cover more real-world application domains.  相似文献   

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