On the Hierarchies for Deterministic, Nondeterministic and Probabilistic Ordered Read-k-times Branching Programs
Kamil Khadiev

TL;DR
This paper investigates the hierarchy of read-$k$-times branching programs, demonstrating increased computational power with larger $k$ for nondeterministic and probabilistic models, and extending known bounds for various widths.
Contribution
It extends hierarchy results for nondeterministic and probabilistic read-$k$-times branching programs to larger $k$, and introduces new lower bound techniques based on functional descriptions and communication complexity.
Findings
Increasing $k$ enhances nondeterministic $k$-OBDD power for polynomial size.
Hierarchies are extended for probabilistic and nondeterministic models up to $k=o(n/\log n)$.
New lower bounds are established for superpolynomial and subexponential width $k$-OBDDs.
Abstract
The paper examines hierarchies for nondeterministic and deterministic ordered read--times Branching programs. The currently known hierarchies for deterministic -OBDD models of Branching programs for are proved by B. Bollig, M. Sauerhoff, D. Sieling, and I. Wegener in 1998. Their lower bound technique was based on communication complexity approach. For nondeterministic -OBDD it is known that, if is constant then polynomial size -OBDD computes same functions as polynomial size OBDD (The result of Brosenne, Homeister and Waack, 2006). In the same time currently known hierarchies for nondeterministic read -times Branching programs for are proved by Okolnishnikova in 1997, and for probabilistic read -times Branching programs for are proved by Hromkovic and Saurhoff in 2003. We show that…
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