Random languages for nonuniform complexity classes
نویسندگان
چکیده
A language A is considered to be random for a class C if for every language B in C the fraction of the strings where A and B coincide is approximately 1/2. We show that there exist languages in DSPACE(f(n)) which are random for the non-uniform class DSPACE(g(n))=h(n), where n, g(n) and h(n) are in o(f(n)). Non-uniform complexity classes were introduced by Karp and Lipton Karp and Lipton 1980] and allow an advice string that depends only on the length of the input as additional information. This paper extends a result by Wilber Wilber 1983] who proved bounds for the existence of random languages for (uniform) time and space classes. Huynh Huynh 1987] provides a result for the special case of P=poly-random languages in EXPSPACE. Here we explore a diierent method using strings with high generalized Kolmogorov complexity Hartmanis 1983]. A characterization of the non-uniform space classes in terms of Kolmogorov complexity is given. This generalizes a result of Balcc azar, D az, and Gabarrr o 1987b] where characterizations of the class PSPACE=poly are given.
منابع مشابه
Automata That Take Advice Automata That Take Advice
Karp and Lipton introduced advice-taking Turing machines to capture nonuniform complexity classes. We study this concept for automata-like models and compare it to other nonuniform models studied in connection with formal languages in the literature. Based on this we obtain complete separations of the classes of the Chomsky hierarchy relative to advices.
متن کاملAutomata That Take Advice
Karp and Lipton introduced advice-taking Turing machines to capture nonuniform complexity classes. We study this concept for automata-like models and compare it to other nonuniform models studied in connection with formal languages in the literature. Based on this we obtain complete separations of the classes of the Chomsky hierarchy relative to advices.
متن کاملSome Structural Complexity Aspects of Neural Computation
Recent work by Siegelmann and Sontag hod demonatrated that polynomial time on linear saturated recurrent neural networks equab polynomial time on standard computational models: !bring machines if the weights of the net are rationab, and nonuniform circuits if the weights are reab. Here we develop further connections between the languages recognized by such neural nets and other complen'ty class...
متن کاملMaking Nondeterminism Unambiguous 1
We show that in the context of nonuniform complexity, nondeterministic logarithmic space bounded computation can be made unambiguous. An analogous result holds for the class of problems reducible to context-free languages. In terms of complexity classes, this can be stated as: NL/poly = UL/poly LogCFL/poly = UAuxPDA(log n; nO(1))/poly
متن کاملTask Complexity Manipulation and Accuracy in Writing Performance
This study aimed to investigate the impact of task sequencing, along +/- reasoning demands dimension, on writing task performance in terms of accuracy. The study was motivated by Robinson’s Cognition Hypothesis (CH) as well as previous studies investigating the relationships between task complexity and second language production. The participants of the study were 90 intermediate students at t...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- J. Complexity
دوره 7 شماره
صفحات -
تاریخ انتشار 1991