Synthesizing efficient systems in probabilistic environments
نویسندگان
چکیده
منابع مشابه
Synthesizing Energy-Efficient Embedded Systems with LOPOCOS
In this paper, we introduce the LOPOCOS (Low Power Co-synthesis) system, a prototype CAD tool for system level co-design. LOPOCOS targets the design of energy-efficient embedded systems implemented as heterogeneous distributed architectures. In particular, it is designed to solve the specific problems involved in architectures that include dynamic voltage scalable (DVS) processors. The aim of t...
متن کاملSynthesizing Probabilistic Composers
Synthesis from components is the automated construction of a composite system from a library of reusable components such that the system satisfies the given specification. This is in contrast to classical synthesis, where systems are always “constructed from scratch”. In the control-flow model of composition, exactly one component is in control at a given time and control is switched to another...
متن کاملSemi-Symbolic Computation of Efficient Controllers in Probabilistic Environments
We present a semi-symbolic algorithm for synthesizing efficient controllers in a stochastic environment, implemented as an add-on to the probabilistic model checker PRISM. The user specifies the environment and the controllable actions using a Markov Decision Process (MDP), modeled in the PRISM language. Controller efficiency is defined with respect to a user-specified assignment of costs and r...
متن کاملSynthesizing Efficient Controllers
In many situations, we are interested in controllers that implement a good trade-off between conflicting objectives, e.g., the speed of a car versus its fuel consumption, or the transmission rate of a wireless device versus its energy consumption. In both cases, we aim for a system that efficiently uses its resources. In this paper we show how to automatically construct efficient controllers. W...
متن کاملSynthesizing Human-Like Walking in Constrained Environments
We present a new algorithm to generate plausible walking motion for high-DOF human-like articulated figures in constrained environments with multiple obstacles. Our approach combines hierarchical model decomposition with samplebased planning to efficiently compute a collision-free path in tight spaces. Furthermore, we use path perturbation and replanning techniques to satisfy the kinematic and ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Acta Informatica
سال: 2015
ISSN: 0001-5903,1432-0525
DOI: 10.1007/s00236-015-0237-y