no code implementations • 26 Apr 2013 • Emad Saad
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 Markov decision processes, and conditional planning.
no code implementations • 6 Apr 2013 • Emad Saad
We present a logical framework to represent and reason about stochastic optimization problems based on probability answer set programming.
no code implementations • 5 Apr 2013 • Emad Saad
We present a logical framework to represent and reason about fuzzy optimization problems based on fuzzy answer set optimization programming.
no code implementations • 5 Apr 2013 • Emad Saad
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.
no code implementations • 5 Apr 2013 • Emad Saad
Fuzzy answer set programming is a declarative framework for representing and reasoning about knowledge in fuzzy environments.
no code implementations • 5 Apr 2013 • Emad Saad
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 in answer set programming.
no code implementations • 5 Apr 2013 • Emad Saad
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.
no code implementations • 5 Apr 2013 • Emad Saad
We show that the proposed probability answer set semantics of DHPP subsumes both the original probability answer set semantics of DHPP and the classical answer set semantics of classical disjunctive logic programs with classical aggregates, and consequently subsumes the classical answer set semantics of the original disjunctive logic programs.