Patrick Henry Winston. Artificial Intelligence. Addison-Wesley, 1992.  Home/Search   Document Not in Database   Summary   Related Articles   Check

....human thinking, activities such as decision making, problem solving, learning . Richard Stottler [Stottler, 1999] defines AI as follows: Artificial intelligence is the mimicking of human thought and cognitive processes to solve complex problems. Patrick Henry Winston s definition of AI in [Winston, 1992] is: Artificial Intelligence is . the study of the computations that make it possible to perceive, reason, and act. From the perspective of this definition, Artificial Intelligence di#ers from most of psychology because of the greater emphasis on computation, Many online ....

Patrick Henry Winston. Artificial Intelligence. Addison Wesley, 3rd edition, 1992.

....solution would require either too many resources, or, the implementing process should be completed with numerous shortcuts. The narrowed focus, and thus, very limited application domain result in difficult compromises when considering handling of free form textual input from individual persons [Win92, Ric91, Rau96]. One additional solution to the classification problem would be the introduction of www forms, which could have enough machine computable information in them so that the processing would be relatively easy and inexpensive. This, however, is not very flexible solution because forms do not ....

Patrick Henry Winston, "Artificial Intelligence", Addison-Wesley, 1992

....solution would require either too many resources, or, the implementing process should be completed with numerous shortcuts. The narrowed focus, and thus, very limited application domain result in difficult compromises when considering handling of free form textual input from individual persons [Win92, Ric91, Rau96]. One additional solution to the classification problem would be the introduction of www forms which could have enough machine computable information in them so that the processing would be relatively easy and inexpensive. This, however, is not a very flexible solution because forms do not ....

Patrick Henry Winston, "Artificial Intelligence", Addison-Wesley, 1992

....Two Application Programs A Line Labeling Benchmark The performance of path based rules relative to pattern matching rules and to C on a wellknown line labeling application program is shown in Table 2. This benchmark program labels line drawings using Waltz s constraint propagation algorithm [24], and has previously been used to evaluate matching algorithms for OPS5 style systems [23, 18, 25, 22] The C5 version of the benchmark is a slightly modified version of a simple OPS5 program obtained from Daniel P. Miranker. 14 Because OPS5 and R have different rule languages, the benchmark ....

Patrick Henry Winston. Artificial Intelligence. Addison-Wesley Publishing Company, Reading, MA, 1984.

....strategy has a unique way of searching through a vast, and often entangled, search space. Sophisticated search procedures, like simulated annealing, may perform very well, but require finetuning of their parameters. Hill climbing is a very simple search strategy that has no parameters. Winston [19] describes improvements such as beam search, best first search and branch and bound. Moreover, he lists characteristics of the search space to which the hill climber is sensitive. These are 3. Smart Hill Climbing 5 foothills (large amounts of local maxima) plateaus (a practically flat search ....

Patrick Henry Winston. Artificial Intelligence. Addison-Wesley, 1977.

.... function (C) in one of the following ways: ffl normalized fitness (a standard measure for fitness computation) If performance of individual i is c(i) 0 (also called standardized fitness) then a normalized fitness measure of individual i is f(i) c(i) P i c(i) 46 ffl rank fitness [Winston, 1992] is given by a geometric probability distribution with probability of success p on the population ranks obtained after sorting the standardized fitness values. Thus rank k will receive a fitness f k = 1 Gamma p) k Gamma1 Delta p It has the advantage that it eliminates the implicit bias ....

Patrick Henry Winston, Artificial Intelligence, 3rd edition, AddisonWesley Pub. Co., 1992.

....two simple examples in R , C5, and C . 18 The performance of path based rules relative to pattern matching rules and to C on a well known line labeling application program is shown in Table 2. This benchmark program labels line drawings using Waltz s constraint propagation algorithm [25], and has previously been used to evaluate matching algorithms for OPS5 style systems [24, 19, 26, 23] input C5 R C size Standard Sets Hash Sets Standard Sets Hash Sets secs MB secs MB secs MB secs MB secs MB 12 166.0 1.0 5.0 1.3 1.0 0.7 3.4 0.7 0.6 0.5 25 737.0 1.7 15.0 2.1 2.5 1.1 13.1 ....

Patrick Henry Winston, Artificial Intelligence, Addison-Wesley Publishing Company, Reading, MA, 1984.

....layer are each connected to all the output neurons (one in this case) This is an example of a fully connected feedforward neural network. Thesis A.R.J. Katz 16 16 Figure 6. Artificial neural network (images from [New1] Feedforward networks of this type can be trained by back propagation [Win2]. This is a procedure that trains the network by making small adjustments to the weights of each neuron in the direction that reduces the error at that neuron s output. In their survey paper, Widrow, Rumelhart and Lehr [Wid1] list many applications of neural networks, including a number in ....

....networks and even quote blood cell classification as one of their examples of well known pattern matching applications of neural networks. The multilayer feedforward network with back propagation is seen as the most popular amongst researchers and neural network users for classification. Winston [Win2], describes a number of limitations of back propagation neural networks: Poor choice of learning rate can cause the network to either become unstable or get stuck on a local minimum in the error surface (as well as being very slow to train) Best choice of learning rate is problem specific. ....

Patrick Henry Winston, "Artificial Intelligence", Third Edition, Addison-Wesley Publishing Company, Reading Massachusetts. Thesis A.R.J. Katz 58 58

....List Delete List Add List D Odd H ; S Even E ; 4. GPS was developed in the late 50 s by Simon and Newell as a model of human problem solving. The GPS procedure for STRIPS planning is given below. 4 4 This specification of the GPS procedure is derived from the description on page 153 of [ Winston, 1984 ] 30 To find a plan ff such that Sigma [ff] Omega do the following: 1. If Sigma is a subset of Omega return the empty plan. 2. Select some operator o i such that some proposition on the add list of o i is a member of Sigma but not a member of Omega 3. Let Omega 0 be the ....

Patrick Winston. Artificial Intelligence, Second Addition. Addison Wesley, 1984. 32

....Together all these assumptions make up what I call the Shannon paradigm. The Minimax algorithm has been described and explained informally too many times to repeat that effort here. Readers unfamiliar with the algorithm should refer to any introductory AI textbook (such as [Rich Knight 91] or [Winston 92]) for a tutorial explanation. Instead, my contribution here will be a more formal treatment that will be suited to our later discussions. 33 2.4.1 Formalization of the minimax propagation rule We assume the game we are considering has two players, which we will refer to as Max and min, and ....

.... with the usage of the term decision tree in machine learning contexts, where it typically means a classification tree of criteria used to categorize different problem instances (for example, in ID3 like systems) In other areas of AI the term decision tree is used in still other ways (cf. [Winston 92]) In this thesis we will restrict our use of the term to the decisionanalysis context. 1. We have not discussed Scout in this paper. See [Pearl 84] for a detailed description and proof of optimality, and [Bodkin 92a] for a correction of the error in the proof. 113 3.3.1 Initial investigations ....

Patrick Henry Winston. Artificial Intelligence, 3rd edition. Addison-Wesley, 1992.

....living dining room Efficiency Number no of rooms no of rooms 2 Figure 1.2.4: Two room efficiency apartments Here, we are appealing to relations of having between concepts, as well as to relations of being . Efficiencies have bedrooms, and this is represented as a 33 See [Winston 1984, Chapter 8] 24 Richmond H. Thomason Ch. 1 relation between the Two Room Efficiency concept and the concept Bedroom of aTwo Room Efficiency. There is a Bedroom concept, which is invoked when we say that the bedroom of an Efficiency is a Bedroom, but there is also a bedroom role, which can be ....

....to reentrancy in feature structures) or relations like linear precedence of morphemes, that apply to special purpose types. The formal theory of networks with roles especially the nonmonotonic theory has not been developed as much as one would like. Informal remarks can be found in [Winston 1984] and [Fahlman 1979] Formalizations of the monotonic case can be found in [Thomason and Touretzky, 1990] and [Guerreiro et al. 1990] Not much has been done towards formalizing the nonmonotonic case. I hope to remedy this at some point in the future but here I can only sketch some of the ideas ....

Patrick Winston. Artificial intelligence, 2nd ed. Addison-Wesley Publishing Co., Reading, Massachusetts, 1984.

....with sequential construction problems is represented as a tree or a directed acyclic graph. An approach that has proven to be effective to illustrate the search strategy implemented in SAGE is to compare this algorithm with a well known AI algorithm for search in DAGs and trees called Beam search [113]. Beam search examines in parallel a number of nearly optimal alternatives (the beam) This search algorithm progresses level by level in the tree of states and it moves downward only from the best w nodes at each level. Consequently, the number of nodes explored remains manageable: if the ....

Patrick Henry Winston. Artificial Intelligence. Addison-Wesley, 1984. Second edition.

....computed by CPPREF itself, most of them are deduced from others by YAKS. For detailed information about this tool, see [34] 4 The SARA Natural Language Processor The effort to implement a sophisticated natural language processor is high. Therefore, we chose to implement a case frame parser [38, 12], which is based on the notion of semantic case [16] and requires only moderate implementation effort compared to other parsing techniques, as for example unificationbased parsing [33] Case frame parsing provides a good starting point for building robust parsers and for handling dialogue ....

Patrick Henry Winston. Artificial Intelligence. Addison Wesley, 1981.

....Abstract Keith H. Randall randall theory.lcs.mit.edu MIT Laboratory for Computer Science 545 Technology Square Cambridge, MA 02139 Many applications including event driven logic simulation [1, 2, 5] spreadsheet calculation, and constraint propagation in artificial intelligence programs [6] maintain a directed acyclic graph (dag) in which each vertex contains a value and each edge represents a data dependency between two values. The value of a vertex is determined by a vertex specific function of the values of the vertex s immediate predecessors. During the execution of the ....

Patrick Henry Winston. Artificial Intelligence. Addison-Wesley, 1992.

....intelligently for the benefit of mankind. IX. Further readings : For readers interested in gaining a better understanding of one of the two fields, fuzzy logic and artificial intelligence, we would like to refer to some good introductory texts such as Winston s book on artificial intelligence [21], or, more recently, McNeill and Freiberger s book on fuzzy logic [14] For those wanting to dig deeper or to answer more elaborate questions, we recommend to consult some of the following texts and media (the list could of course be much longer, but we limit ourselves to the most accessible ....

Patrick Henry Winston. Artificial Intelligence. Addison-Wesley Publishing Company, Inc., 1977.

....offspring 2. Nevertheless, nature produces individuals with different traits 3. The fittest individuals those with the most favourable traits tend to have more offspring than do those with unfavourable traits. This drives the population as a whole towards favourable traits. 1 taken from [Winston 92] CHAPTER 3. INTRODUCTION TO GENETIC ALGORITHMS 27 4. Over a long period, variation can accumulate, producing entirely new species whose traits make them especially suited to particular ecological niches. Parents which adapt better are more likely to be selected for producing children. The ....

Patrick Winston. Artificial Intelligence, 3rd edition. Addison Wesley Publishing Company, 1992.

....the search method tends to a top down approach. Fitting all the above mentioned types of knowledge in a single knowledge representation scheme would involve compromising and would thus result in a sub optimal solution. The general strategy can be well represented using a goal reduction scheme [6]. The generic constraints will be expressed by human photo interpretation experts. They will use natural language rules, based on vague terms. This set of rules will be imposed using a fuzzy production rule system. The knowledge related to each object type is necessary when evaluating or ....

Patrick-Henry Winston, "Artificial Intelligence", AddisonWesley, 2 edition, 1984.

....knowledge in a single representation scheme would involve compromising and would thus result in a sub optimal solution. Therefore different knowledge types are encoded independently using in each case the best suited formalism. The general strategy is well represented using a goal reduction scheme [6]. The generic constraints are usually expressed by human experts (image analysts) They use natural language rules, based on vague terms. This set of rules is encoded using a fuzzy production rule system. The knowledge related to each object type is necessary when evaluating or extracting a single ....

Patrick-Henry Winston, "Artificial Intelligence", Addison-Wesley, 2 edition, 1984.

....needed. These are discussed in detail in the next chapter, and following that is the specific design of a prototype model selection program. Chapter 6 Frames, Case based Reasoning and Rough Sets The concept of Artificial Intelligence (AI) is described in a number of general AI books, such as [Win92, RN95, LS93], and will not be discussed here. The purpose of this chapter is to describe parts of AI found useful for the problems of Decision Support Systems, Operations Management and Model Management discussed in the previous chapters. We focus on the concepts Case based Reasoning and Rough Sets. Further ....

....in the previous chapters. We focus on the concepts Case based Reasoning and Rough Sets. Further reading on related techniques and methodologies such as decision trees and the ID3 algorithm [Qui79, Qui86] Bayesian probability theory or Belief Networks can be found in a number of books, including [Win92, RN95, LS93]. First, we discuss frames, which is a representation suitable for storing hierarchical information. Afterwards, Case based Reasoning (CBR) is discussed. CBR is a framework for learning from previous cases and utilising this knowledge when faced with new cases. This may be useful for the model ....

Patrick H. Winston. Artificial Intelligence. Addison-Wesley, third edition, 1992. 737 pages.

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Patrick H. Winston. "Artificial Intelligence" 3rd edition Addison Wesley.

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Patrick Henry Winston. Artificial Intelligence. Addison-Wesley, 1992.

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Patrick H. Winston, Artificial Intelligence, Addison-Wesley Publishing Company, Inc., 1977

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Patrick H. Winston. Artificial Intelligence. Addison-Wesley, Reading, Mass, 2nd edition, 1984.

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Patrick Winston. 1993. Artificial Intelligence. 3rd Edition. Addison Wesley.

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Patrick H. Winston. Artificial Intelligence. Addison-Wesley, Reading, Mass, 2nd edition, 1984.

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