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pro vyhledávání: '"Saad, Emad"'
Autor:
Saad, Emad
Non deterministic applications arise in many domains, including, stochastic optimization, multi-objectives optimization, stochastic planning, contingent stochastic planning, reinforcement learning, reinforcement learning in partially observable Marko
Externí odkaz:
http://arxiv.org/abs/1304.7168
Autor:
Saad, Emad
We present a logical framework to represent and reason about stochastic optimization problems based on probability answer set programming. This is established by allowing probability optimization aggregates, e.g., minimum and maximum in the language
Externí odkaz:
http://arxiv.org/abs/1304.3489
Autor:
Saad, Emad
We present a unified logical framework for representing and reasoning about both probability quantitative and qualitative preferences in probability answer set programming, called probability answer set optimization programs. The proposed framework i
Externí odkaz:
http://arxiv.org/abs/1304.3144
Autor:
Saad, Emad
We allow representing and reasoning in the presence of nested multiple aggregates over multiple variables and nested multiple aggregates over functions involving multiple variables in answer sets, precisely, in answer set optimization programming and
Externí odkaz:
http://arxiv.org/abs/1304.2799
Autor:
Saad, Emad
We present a unified logical framework for representing and reasoning about both quantitative and qualitative preferences in fuzzy answer set programming, called fuzzy answer set optimization programs. The proposed framework is vital to allow definin
Externí odkaz:
http://arxiv.org/abs/1304.2797
Autor:
Saad, Emad
We present a logical framework to represent and reason about fuzzy optimization problems based on fuzzy answer set optimization programming. This is accomplished by allowing fuzzy optimization aggregates, e.g., minimum and maximum in the language of
Externí odkaz:
http://arxiv.org/abs/1304.2384
Autor:
Saad, Emad
Fuzzy answer set programming is a declarative framework for representing and reasoning about knowledge in fuzzy environments. However, the unavailability of fuzzy aggregates in disjunctive fuzzy logic programs, DFLP, with fuzzy answer set semantics p
Externí odkaz:
http://arxiv.org/abs/1304.1827
Autor:
Saad, Emad
Probability answer set programming is a declarative programming that has been shown effective for representing and reasoning about a variety of probability reasoning tasks. However, the lack of probability aggregates, e.g. {\em expected values}, in t
Externí odkaz:
http://arxiv.org/abs/1304.1684
Autor:
Saad, Emad
Knowledge Representation is important issue in reinforcement learning. In this paper, we bridge the gap between reinforcement learning and knowledge representation, by providing a rich knowledge representation framework, based on normal logic program
Externí odkaz:
http://arxiv.org/abs/1012.1552
Autor:
Saad, Emad
We present a probabilistic logic programming framework to reinforcement learning, by integrating reinforce-ment learning, in POMDP environments, with normal hybrid probabilistic logic programs with probabilistic answer set seman-tics, that is capable
Externí odkaz:
http://arxiv.org/abs/1011.5951