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Neuro Symbolic AI for Sequential Decision Making
Deep learning based approaches have been used to address several problems of a sequential nature, whether using supervised learning to learn a model...
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NeuroSynt: A Neuro-symbolic Portfolio Solver for Reactive Synthesis
We introduce NeuroSynt, a neuro-symbolic portfolio solver framework for reactive synthesis. At the core of the solver lies a seamless integration of...
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Symbolic Path-Guided Test Cases for Models with Data and Time
This paper focuses on generating test cases from timed symbolic transition systems. At the heart of the generation process are symbolic execution...
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Intraprocedural Analysis Based on Symbolic Execution for Bug Detection
AbstractIn this paper, we overview the approaches and techniques employed by the Svace static analysis tool for intraprocedural analysis. This...
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Symbolic Automata
This chapter proposes automata with symbolic state to describe properties, arguing that such an approach allows better abstraction than the event...
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Learning Symbolic Timed Models from Concrete Timed Data
We present a technique for learning explainable timed automata from passive observations of a black-box function, such as an artificial intelligence...
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Detect, Understand, Act: A Neuro-symbolic Hierarchical Reinforcement Learning Framework
In this paper we introduce Detect, Understand, Act (DUA), a neuro-symbolic reinforcement learning framework. The Detect component is composed of a...
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Purely Symbolic Induction of Structure
Techniques honed for the induction of grammar from text corpora can be extended to visual, auditory and other sensory domains, providing a structure...
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Open writer identification from offline handwritten signatures by jointing the one-class symbolic data analysis classifier and feature-dissimilarities
Usually, a large number of reference signatures are required for building the writing style model from offline handwritten signatures (OHSs)....
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Symbolic Solution of Emerson-Lei Games for Reactive Synthesis
Emerson-Lei conditions have recently attracted attention due to both their succinctness and their favorable closure properties. In the current work,...
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Guiding Symbolic Execution with A-Star
Symbolic execution is widely used to detect vulnerabilities in software. The idea is to symbolically execute the program in order to find an...
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FDSE: Enhance Symbolic Execution by Fuzzing-based Pre-Analysis (Competition Contribution)
FDSE serves as an automatic test generation tool designed for C programs based on symbolic execution. FDSE employs fuzzing-based pre-analysis and...
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Robotic Choreography Creation Through Symbolic AI Techniques
Symbolic Artificial Intelligence (AI) techniques in robotic choreography contribute to the broader field of human-robot interaction and address the...
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Symbolic Computation in Automated Program Reasoning
We describe applications of symbolic computation towards automating the formal analysis of while-programs implementing polynomial arithmetic. We...
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Tool Paper - SEMA: Symbolic Execution Toolchain for Malware Analysis
Today, malware threats are more dangerous than ever with thousand of new samples emerging everyday. There exists a wide range of static and dynamic...
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SymPas: Symbolic Program Slicing
Program slicing is a technique for simplifying programs by focusing on selected aspects of their behavior. Current mainstream static slicing methods...
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Symbolic-Numeric Computation in Modeling the Dynamics of the Many-Body System TRAPPIST
Modeling the dynamics of the exoplanetary system TRAPPIST with seven bodies of variable mass moving around a central parent star along quasi-elliptic...
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Symbolic Domains and Reachability for Nets with Trajectories
This paper considers verification of timed models handling additional quantities progressing linearly such as distance of moving objects to a target....
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Explainable Fraud Detection with Deep Symbolic Classification
There is a growing demand for explainable, transparent, and data-driven models within the domain of fraud detection. Decisions made by the fraud...
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A Systematic Literature Review on Smart Contract Vulnerability Detection by Symbolic Execution
Symbolic execution emerges as a potent method for software testing, progressively tackling the unique complexities associated with smart contract...