Search Results for author: Moshe Vardi

Found 5 papers, 1 papers with code

Constraint-Driven Explanations of Black-Box ML Models

no code implementations1 Jan 2021 Aditya Aniruddha Shrotri, Nina Narodytska, Alexey Ignatiev, Joao Marques-Silva, Kuldeep S. Meel, Moshe Vardi

Modern machine learning techniques have enjoyed widespread success, but are plagued by lack of transparency in their decision making, which has led to the emergence of the field of explainable AI.

Decision Making

LTLf Synthesis with Fairness and Stability Assumptions

no code implementations17 Dec 2019 Shufang Zhu, Giuseppe De Giacomo, Geguang Pu, Moshe Vardi

A key observation here is that even if we consider systems with LTLf goals on finite traces, environment assumptions need to be expressed over infinite traces, since accomplishing the agent goals may require an unbounded number of environment action.

Fairness

Learning to Solve NP-Complete Problems - A Graph Neural Network for Decision TSP

3 code implementations8 Sep 2018 Marcelo O. R. Prates, Pedro H. C. Avelar, Henrique Lemos, Luis Lamb, Moshe Vardi

Our model is trained to function as an effective message-passing algorithm in which edges (embedded with their weights) communicate with vertices for a number of iterations after which the model is asked to decide whether a route with cost $<C$ exists.

Graph Neural Network

Constrained Sampling and Counting: Universal Hashing Meets SAT Solving

no code implementations21 Dec 2015 Kuldeep S. Meel, Moshe Vardi, Supratik Chakraborty, Daniel J. Fremont, Sanjit A. Seshia, Dror Fried, Alexander Ivrii, Sharad Malik

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.

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