Not logged in : Login
(Sponging disallowed)

About: Formal Verification of Neural Agents in Non-deterministic Environments     Goto   Sponge   NotDistinct   Permalink

An Entity of Type : bibo:AcademicArticle, within Data Space : linkeddata.uriburner.com:28898 associated with source document(s)

AttributesValues
type
seeAlso
sameAs
Title
  • Formal Verification of Neural Agents in Non-deterministic Environments
described by
Date
  • 2020-05-09
Creator
status
Publisher
abstract
  • We introduce a model for agent-environment systems where the agents are implemented via feed-forward ReLU neural networks and the environment is non-deterministic. We study the verification problem of such systems against CTL properties. We show that verifying these systems against reachability properties is undecidable. We introduce a bounded fragment of CTL, show its usefulness in identifying shallow bugs in the system, and prove that the verification problem against specifications in bounded CTL is in coNEXPTIME and PSPACE-hard. We present a novel parallel algorithm for MILP-based verification of agent-environment systems, present an implementation, and report the experimental results obtained against a variant of the VerticalCAS use-case.
Is Part Of
Subject
list of authors
presented at
is topic of
is primary topic of
Faceted Search & Find service v1.17_git144 as of Jul 26 2024


Alternative Linked Data Documents: iSPARQL | ODE     Content Formats:   [cxml] [csv]     RDF   [text] [turtle] [ld+json] [rdf+json] [rdf+xml]     ODATA   [atom+xml] [odata+json]     Microdata   [microdata+json] [html]    About   
This material is Open Knowledge   W3C Semantic Web Technology [RDF Data] Valid XHTML + RDFa
OpenLink Virtuoso version 08.03.3331 as of Aug 25 2024, on Linux (x86_64-ubuntu_noble-linux-glibc2.38-64), Single-Server Edition (378 GB total memory, 16 GB memory in use)
Data on this page belongs to its respective rights holders.
Virtuoso Faceted Browser Copyright © 2009-2024 OpenLink Software