Genetic Programming on Program Traces as an Inference Engine for Probabilistic Languages
Created by W.Langdon from
gp-bibliography.bib Revision:1.8051
- @InProceedings{conf/agi/BatishchevaP15,
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author = "Vita Batishcheva and Alexey Potapov",
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title = "Genetic Programming on Program Traces as an Inference
Engine for Probabilistic Languages",
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booktitle = "Proceedings of the 8th International Conference
Artificial General Intelligence, AGI 2015",
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year = "2015",
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editor = "Jordi Bieger and Ben Goertzel and Alexey Potapov",
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volume = "9205",
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series = "Lecture Notes in Computer Science",
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pages = "14--24",
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address = "Berlin, Germany",
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month = jul # " 22-25",
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publisher = "Springer",
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keywords = "genetic algorithms, genetic programming, Probabilistic
programming, Program traces",
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isbn13 = "978-3-319-21364-4",
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bibdate = "2015-07-16",
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bibsource = "DBLP,
http://dblp.uni-trier.de/db/conf/agi/agi2015.html#BatishchevaP15",
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URL = "http://dx.doi.org/10.1007/978-3-319-21365-1",
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DOI = "doi:10.1007/978-3-319-21365-1_2",
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abstract = "Methods of simulated annealing and genetic programming
over probabilistic program traces are developed
firstly. These methods combine expressiveness of
Turing-complete probabilistic languages, in which
arbitrary generative models can be defined, and search
effectiveness of meta-heuristic methods. To use these
methods, one should only specify a generative model of
objects of interest and a fitness function over them
without necessity to implement domain-specific genetic
operators or mappings from objects to and from bit
strings. On the other hand, implemented methods showed
better quality than the traditional mh-query on several
optimization tasks. Thus, these results can contribute
to both fields of genetic programming and probabilistic
programming.",
- }
Genetic Programming entries for
Vita Batishcheva
Alexey Potapov
Citations