P. H. Winston. Artificial Intelligence. Addison-Wesley, Reading, MA, 1992. Home/Search Document Not in Database Summary Related Articles Check |
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STUDIA UNIV. BABES--BOLYAI, INFORMATICA, Volume XLVII.. - Lasg Logic Architecture (2002) (Correct)
....as well. 2. A Logic Architecture Based on Stacks of Goals (LASG) We will consider, in the following, the case of an agent which goal is to solve a given problem (to bring the problem from an initial to a final state) based on a set of operators (rules) that could be applied on a given moment [4]. In a LASG architecture, we will use the declarative representation of the knowledge. Let L be a set of sentences from the first order logic, and D = P(L) the set of L databases (the set of sets of L formulae) In the model that we propose, the internal state of the agent will be given by an ....
....state (Xf, Yf) the non deterministic predicate solution(Xi, Yi, L1, L, M, N) i, i, i, o, i) collects the elements of a solution in L (L1 is the former generated list) The goal has the form goal: path(4, 1, 1, 3, 4, 3, L) and the solutions are two: Figure 4. The Prolog program L= [4, 1], 3, 1] 2, 1] 2, 2] 1, 2] 1, 3] 6. Conclusions and further work In a logic based architecture, the intelligent behavior is generated by a symbolic representation of the environment and the agent s behavior, and by a symbolic manipulation of this representation. In the logic based ....
Winston, P., "Artificial Intelligence", Addison Wesley, Reading, MA, 1984, 2nd ed Babes-Bolyai University, Cluj-Napoca, Romania E-mail address: gabis@cs.ubbcluj.ro
The Emergence of Higher Levels of Description - Chris Thornton Cognitive (Correct)
....for a collection of entities all of which can be understood in terms of situated blocks (i.e. particular blocks at particular locations in a particular blocksworld) are shown in the figure below. These include representations for the level 1 entity arch and the level 2 entity arcade (cf. [5,6]) The function that produces properties of arches is 3 place since an arch is made up of a set of three blocks which are related together in a certain way. The root of the representation of arcade is a 7 place function, the assumption being that any arcade is made up of a collection of seven ....
Winston, P. (1984). Artificial Intelligence (2nd edn). Reading, Mass.: Addison-Wesley.
Learning Pronunciation Rules for English Graphemes Using the.. - Hamilton, Zhang (1994) (1 citation) (Correct)
....form. A relationship is described as a set of conditions on the syllable containing the grapheme. In Figure 1, we show the relationship between the grapheme a and the IPA symbols [ei] ash] and [schwa] The LEP G learning algorithm is based on the Version Space algorithm (VSA) Mitchell, 1982, Winston, 1992] with our modifications. For each grapheme and its target IPA symbol, we input a set of positive and negative examples. LEP G chooses, from the version space, the single hypothesis that is consistent with these examples, and this hypothesis becomes one of the pronunciation rules. Before a rule is ....
....are made. We have to make sure that no new general hypothesis is a generalization of some other general hypothesis, no new general hypothesis is a generalization of the negative example N 1 , and no new general hypothesis has a field which is more specific than the current specific hypothesis [Winston, 1992]. Now, let CSH denote the current specific hypothesis, CGH denote the current general hypothesis, and F i denote each field in CSH, CGH, or N j (negative examples) where i is an index of fields and j is an index of the negative examples. There are three conditions under which no new hypothesis ....
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Winston, P. (1992). Artificial Intelligence, Third Edition. Addison-Wesley, Reading, MA.
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P. H. Winston. Artificial Intelligence. Addison-Wesley, Reading, MA, 1992.
A Bayesian Framework For Considering Probability Distributions - Of Image Segments (Correct)
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P. H. Winston, Artificial Intelligence. Reading, MA: Addison-Wesley, 1984.
Volume Xxx, (2001 ) Number Yyy Pp. ??--?? - Incremental Line Labelling (Correct)
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P.H. Winston, Artificial Intelligence (3rd ed.), Addison Wesley (1992).
Hunter-Gatherer: Applying Constraint Satisfaction.. - Beale (1997) (6 citations) (Correct)
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P.H. Winston. 1984. Artificial Intelligence Addison-Wesley, Readig, MA.
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Winston, P. H., Artificial Intelligence, Reading, MA: Addison Wesley Publishing Co., 1992.
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Winston, P. H. 1984. Artificial Intelligence. Addison--Wesley.
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Winston, P.H.(1977).Artificial intelligence. Reading, MA: Addison-Wesley.
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Winston P.: Artificial Intelligence. 3rd ed, Addison Wesley (1992)
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H.W. Winston. Artificial Intelligence (2nd edn). Addison-Wesley, Reading, MA, 1984.
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P.H. Winston. Artificial Intelligence. Addison-Wesley, 1977. Referred to in page(s) 18, 23, 24, 25.
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P. H. Winston, Artificial Intelligence, Addison Wesley (1984).
Multi-Hierarchical Learning-Based Cosimulation - Tudor Niculiu Politehnica (Correct)
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P. Winston, Artificial Intelligence, 3rd Edition (Reading, Ma: Addison-Wesley, 1992).
Modeling Multistep Cyber Attacks for Scenario Recognition - Cheung, Lindqvist, Fong (2003) (1 citation) (Correct)
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P. H. Winston. Artificial Intelligence. Addison-Wesley, 1977.
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Winston, P. H. Artificial Intelligence. 3rd Edition. Addison-Wesley. 1992.
Visual Abstraction in Analogical Problem Solving: A Dissertation.. - Davies (Correct)
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Winston, P. H. (1992). Artificial Intelligence. Addison-Wesley Publishing, Reading, Massachusetts.
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