Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Practical problems often combine real-world hard constraints with soft constraints involving preferences, uncertainties or flexible requirements. A probability distribution over the models that meet the hard constraints is an ansr to such problems that is in the spirit of incorporating soft constraints.#R##N##R##N# propose a method using SAT-based reasoning, probabilistic reasoning and linear programming that computes such a distribution when soft constraints are interpreted as constraints whose violation is bound by a given probability. The method, called Optimized Probabilistic Satisfiability (oPSAT), consists of a two-phase computation of a probability distribution over the set of valuations of a SAT formula. Algorithms for both phases are presented and their complexity is discussed.#R##N##R##N# also describe an application of the oPSAT technique to the problem of combinatorial materials discovery.
['Marcelo Finger', 'Ronan Le Bras', 'Carla P. Gomes', 'Bart Selman']
I am writing a research paper on a idea Solutions for hard and soft constraints using optimized probabilistic satisfiability
[{"from": "human", "value": "I am writing a research paper on a idea Solutions for hard and soft constraints using optimized probabilistic satisfiability"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Practical problems often combine real-world hard constraints with soft constraints involving preferences, uncertainties or flexible requirements. A probability distribution over the models that meet the hard constraints is an ansr to such problems that is in the spirit of incorporating soft constraints.#R##N##R##N# propose a method using SAT-based reasoning, probabilistic reasoning and linear programming that computes such a distribution when soft constraints are interpreted as constraints whose violation is bound by a given probability. The method, called Optimized Probabilistic Satisfiability (oPSAT), consists of a two-phase computation of a probability distribution over the set of valuations of a SAT formula. Algorithms for both phases are presented and their complexity is discussed.#R##N##R##N# also describe an application of the oPSAT technique to the problem of combinatorial materials discovery."}]