3,740 research outputs found
Distributed Logic Objects: A Fragment of Rewriting Logic and its Implementation
Abstract This paper presents a logic language (called Distributed Logic Objects, DLO for short) that supports objects, messages and inheritance. The operational semantics of the language is given in terms of rewriting rules acting upon the (possibly distributed) state of the system. In this sense, the logic underlying the language is Rewriting Logic. In the paper we discuss the implementation of this language on distributed memory MIMD architectures, and we describe the advantages achieved in terms of flexibility, scalability and load balancing. In more detail, the implementation is obtained by translating logic objects into a concurrent logic language based on multi-head clauses, taking advantage from its distributed implementation on a massively parallel architecture. In the underlying implementation, objects are clusters of processes, objects' state is represented by logical variables, message-passing communication between objects is performed via multi-head clauses, and inheritance is mapped into clause union. Some interesting features such as transparent object migration and intensional messages are easily achieved thanks to the underlying support. In the paper, we also sketch a (direct) distributed implementation supporting the indexing of clauses for single-named methods
Logic-Based Specification Languages for Intelligent Software Agents
The research field of Agent-Oriented Software Engineering (AOSE) aims to find
abstractions, languages, methodologies and toolkits for modeling, verifying,
validating and prototyping complex applications conceptualized as Multiagent
Systems (MASs). A very lively research sub-field studies how formal methods can
be used for AOSE. This paper presents a detailed survey of six logic-based
executable agent specification languages that have been chosen for their
potential to be integrated in our ARPEGGIO project, an open framework for
specifying and prototyping a MAS. The six languages are ConGoLog, Agent-0, the
IMPACT agent programming language, DyLog, Concurrent METATEM and Ehhf. For each
executable language, the logic foundations are described and an example of use
is shown. A comparison of the six languages and a survey of similar approaches
complete the paper, together with considerations of the advantages of using
logic-based languages in MAS modeling and prototyping.Comment: 67 pages, 1 table, 1 figure. Accepted for publication by the Journal
"Theory and Practice of Logic Programming", volume 4, Maurice Bruynooghe
Editor-in-Chie
Coherent Integration of Databases by Abductive Logic Programming
We introduce an abductive method for a coherent integration of independent
data-sources. The idea is to compute a list of data-facts that should be
inserted to the amalgamated database or retracted from it in order to restore
its consistency. This method is implemented by an abductive solver, called
Asystem, that applies SLDNFA-resolution on a meta-theory that relates
different, possibly contradicting, input databases. We also give a pure
model-theoretic analysis of the possible ways to `recover' consistent data from
an inconsistent database in terms of those models of the database that exhibit
as minimal inconsistent information as reasonably possible. This allows us to
characterize the `recovered databases' in terms of the `preferred' (i.e., most
consistent) models of the theory. The outcome is an abductive-based application
that is sound and complete with respect to a corresponding model-based,
preferential semantics, and -- to the best of our knowledge -- is more
expressive (thus more general) than any other implementation of coherent
integration of databases
Verification of the Tree-Based Hierarchical Read-Copy Update in the Linux Kernel
Read-Copy Update (RCU) is a scalable, high-performance Linux-kernel
synchronization mechanism that runs low-overhead readers concurrently with
updaters. Production-quality RCU implementations for multi-core systems are
decidedly non-trivial. Giving the ubiquity of Linux, a rare "million-year" bug
can occur several times per day across the installed base. Stringent validation
of RCU's complex behaviors is thus critically important. Exhaustive testing is
infeasible due to the exponential number of possible executions, which suggests
use of formal verification.
Previous verification efforts on RCU either focus on simple implementations
or use modeling languages, the latter requiring error-prone manual translation
that must be repeated frequently due to regular changes in the Linux kernel's
RCU implementation. In this paper, we first describe the implementation of Tree
RCU in the Linux kernel. We then discuss how to construct a model directly from
Tree RCU's source code in C, and use the CBMC model checker to verify its
safety and liveness properties. To our best knowledge, this is the first
verification of a significant part of RCU's source code, and is an important
step towards integration of formal verification into the Linux kernel's
regression test suite.Comment: This is a long version of a conference paper published in the 2018
Design, Automation and Test in Europe Conference (DATE
Logical Reduction of Metarules
International audienceMany forms of inductive logic programming (ILP) use metarules, second-order Horn clauses, to define the structure of learnable programs and thus the hypothesis space. Deciding which metarules to use for a given learning task is a major open problem and is a trade-off between efficiency and expressivity: the hypothesis space grows given more metarules, so we wish to use fewer metarules, but if we use too few metarules then we lose expressivity. In this paper, we study whether fragments of metarules can be logically reduced to minimal finite subsets. We consider two traditional forms of logical reduction: subsumption and entailment. We also consider a new reduction technique called derivation reduction, which is based on SLD-resolution. We compute reduced sets of metarules for fragments relevant to ILP and theoretically show whether these reduced sets are reductions for more general infinite fragments. We experimentally compare learning with reduced sets of metarules on three domains: Michalski trains, string transformations, and game rules. In general, derivation reduced sets of metarules outperform subsumption and entailment reduced sets, both in terms of predictive accuracies and learning times
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