Dror Fried
YOU?
Author Swipe
View article: Algorithmic Perspective on Toda's Theorem
Algorithmic Perspective on Toda's Theorem Open
Toda's Theorem is a fundamental result in computational complexity theory, whose proof relies on a reduction from a QBF problem with a constant number of quantifiers to a model counting problem. While this reduction, henceforth called Toda…
View article: Mimicking Behaviors in Separated Domains (Abstract Reprint)
Mimicking Behaviors in Separated Domains (Abstract Reprint) Open
Devising a strategy to make a system mimic behaviors from another system is a problem that naturally arises in many areas of Computer Science. In this work, we interpret this problem in the context of intelligent agents, from the perspecti…
View article: On Dependent Variables in Reactive Synthesis
On Dependent Variables in Reactive Synthesis Open
Given a Linear Temporal Logic (LTL) formula over input and output variables, reactive synthesis requires us to design a deterministic Mealy machine that gives the values of outputs at every time step for every sequence of inputs, such that…
View article: On Dependent Variables in Reactive Synthesis
On Dependent Variables in Reactive Synthesis Open
Given a Linear Temporal Logic (LTL) formula over input and output variables, reactive synthesis requires us to design a deterministic Mealy machine that gives the values of outputs at every time step for every sequence of inputs, such that…
View article: Mimicking Behaviors in Separated Domains
Mimicking Behaviors in Separated Domains Open
Devising a strategy to make a system mimic behaviors from another system is a problem that naturally arises in many areas of Computer Science. In this work, we interpret this problem in the context of intelligent agents, from the perspecti…
View article: Algorithmic Foundations of Inexact Computing
Algorithmic Foundations of Inexact Computing Open
Inexact computing also referred to as approximate computing is a style of designing algorithms and computing systems wherein the accuracy of correctness of algorithms executing on them is deliberately traded for significant resource saving…
View article: Deep Learning Models for Automated Classification of Dog Emotional States from Facial Expressions
Deep Learning Models for Automated Classification of Dog Emotional States from Facial Expressions Open
Similarly to humans, facial expressions in animals are closely linked with emotional states. However, in contrast to the human domain, automated recognition of emotional states from facial expressions in animals is underexplored, mainly du…
View article: Mimicking Behaviors in Separated Domains
Mimicking Behaviors in Separated Domains Open
Devising a strategy to make a system mimicking behaviors from another system is a problem that naturally arises in many areas of Computer Science. In this work, we interpret this problem in the context of intelligent agents, from the persp…
View article: Sequential Relational Decomposition
Sequential Relational Decomposition Open
The concept of decomposition in computer science and engineering is considered a fundamental component of computational thinking and is prevalent in design of algorithms, software construction, hardware design, and more. We propose a simpl…
View article: Repeated-Task Canadian Traveler Problem
Repeated-Task Canadian Traveler Problem Open
In the Canadian Traveler Problem (CTP) a traveling agent is given a weighted graph, where some of the edges may be blocked, with a known probability. The agent needs to travel to a given goal. A solution for CTP is a policy, that has the s…
View article: Adapting Behaviors via Reactive Synthesis
Adapting Behaviors via Reactive Synthesis Open
In the \emph{Adapter Design Pattern}, a programmer implements a \emph{Target} interface by constructing an \emph{Adapter} that accesses an existing \emph{Adaptee} code. In this work, we present a reactive synthesis interpretation to the ad…
View article: Adapting Behaviors via Reactive Synthesis
Adapting Behaviors via Reactive Synthesis Open
In the Adapter Design Pattern , a programmer implements a Target interface by constructing an Adapter that accesses an existing Adaptee code. In this work, we present a reactive synthesis interpretation to the adapter design pattern, where…
View article: Taming Discrete Integration via the Boon of Dimensionality
Taming Discrete Integration via the Boon of Dimensionality Open
Discrete integration is a fundamental problem in computer science that concerns the computation of discrete sums over exponentially large sets. Despite intense interest from researchers for over three decades, the design of scalable techni…
View article: Transformations of Boolean Functions
Transformations of Boolean Functions Open
Boolean functions are characterized by the unique structure of their solution space. Some properties of the solution space, such as the possible existence of a solution, are well sought after but difficult to obtain. To better reason about…
View article: Functional Synthesis via Input-Output Separation
Functional Synthesis via Input-Output Separation Open
Boolean functional synthesis is the process of constructing a Boolean function from a Boolean specification that relates input and output variables. Despite significant recent developments in synthesis algorithms, Boolean functional synthe…
View article: Sequential Relational Decomposition
Sequential Relational Decomposition Open
The concept of decomposition in computer science and engineering is considered a fundamental component of computational thinking and is prevalent in design of algorithms, software construction, hardware design, and more. We propose a simpl…
View article: An optimal approximation of discrete random variables with respect to the Kolmogorov distance
An optimal approximation of discrete random variables with respect to the Kolmogorov distance Open
We present an algorithm that takes a discrete random variable $X$ and a number $m$ and computes a random variable whose support (set of possible outcomes) is of size at most $m$ and whose Kolmogorov distance from $X$ is minimal. In additio…
View article: Constrained Sampling and Counting: Universal Hashing Meets SAT Solving
Constrained Sampling and Counting: Universal Hashing Meets SAT Solving Open
Constrained sampling and counting are two fundamental problems in artificial intelligence with a diverse range of applications, spanning probabilistic reasoning and planning to constrained-random verification. While the theory of these pro…
View article: This Time the Robot Settles for a Cost: A Quantitative Approach to Temporal Logic Planning with Partial Satisfaction
This Time the Robot Settles for a Cost: A Quantitative Approach to Temporal Logic Planning with Partial Satisfaction Open
The specification of complex motion goals through temporal logics is increasingly favored in robotics to narrow the gap between task and motion planning. A major limiting factor of such logics, however, is their Boolean satisfaction condit…