1,721,001 research outputs found
The computational behaviour of the SCIFF abductive proof procedure and the SOCS-SI system
No full textThe high computational cost of abduction has limited the application
of this powerful and expressive formalism to practical cases.
SCIFF is an abductive proof procedure used for verifying the
compliance of agent behaviour to interaction protocols in multi-agent
systems; SCIFF has been integrated in SOCS-SI, a system able to
observe the agent interaction, pass it to SCIFF for the reasoning
process and to display in a GUI the results of the SCIFF
computation.
In order to assess the applicability of sciff and SOCS-SI to
practical cases, we have evaluated qualitatively and experimentally
(not yet formally) their computational behaviour, concerning
limitations and scalability. In this paper we show the results of
the analysis
The CHR-based implementation of a system for generation and confirmation of hypotheses
No full textHypothetical reasoning makes it possible to reason with incomplete
information in a wide range of knowledge-based applications.
It is usually necessary to constrain the generation of hypotheses, so to
avoid inconsistent sets or to infer new hypotheses from already made
ones. These requirements are met by several abductive frameworks. In
order to tackle many practical cases, however, it would also be desirable
to support the dynamical acquisition of new facts, which can confirm
the hypotheses, or possibly disconfirm them, leading to the generation
of alternative sets of hypotheses.
In this paper, we present a system which supports the generation of
hypotheses, as well as their confirmation or disconfirmation. We also
describe the implementation of an abductive proof procedure, used as a
reasoning engine for the generation and (dis)confirmation of hypotheses
Testing guidelines conformance by translating a graphical language to computational logic
No full textIn this work we present GOSpeL, a simple graphical language
for modeling guidelines in a flow-chart fashion, and an algorithm
capable of translating a GOSpeL model to a formal language
based on computational logic and abductive logic programming in
particular. The main advantage of this formalism lies in its operational proof-theoretic counterpart, which is able to verify the conformance of a given guideline execution w.r.t. the model, both at runtime or a posteriori. The feasibility of the approach has been tested on fragments of cancer screening protocols
A Verifiable Logic-Based Agent Architecture
No full textIn this paper, we present the SCIFF platform for multi-agent systems.
The platform is based on Abductive Logic Programming, with a uniform language for specifying agent policies and interaction protocols. A significant advantage of the computational logic foundation of the SCIFF framework is that the declarative specifications of agent policies and interaction protocols can be used directly, at runtime, as the programs for the agent instances and for the verification of compliance.
We also provide a definition of conformance of an agent policy to an interaction protocol (i.e., a property that guarantees that an agent will comply to a given protocol) and a operational procedure to test conformance
Argumentation in the Semantic Web
No full textThis article identifies an important role that argumentation should play in the development of the Semantic Web vision. It proposes the ArgSCIFF architecture, which supports high-level reasoning and argumentation-driven interaction among Semantic Web services. ArgSCIFF is based on a concrete, implemented operational model. The authors demonstrate the architecture's ideas and functioning by way of a running example
Generating synthetic positive and negative business process traces through abduction
Full text linkAs recent years have seen the rise of a new discipline commonly addressed as process mining, focused on the management of business processes, two tasks have gained increasing attention in research: process discovery and compliance monitoring. In both these fields, the demand for event log benchmarks with predefined characteristics has determined the design of various methodologies and tools for synthetic log generation. However, artificially created as well as real-life logs often contain positive examples only (i.e. process instances deemed as compliant w.r.t. the model), while the presence of negative process instances (i.e. non-compliant traces) can be crucial to correctly evaluate the performance and robustness of a novel process discovery or conformance checking technique. In this work, we investigate positive and negative trace generation in case of both declarative and procedural model specifications and we present our abduction-based approach to log synthesis. The theoretical study is concretely applied in a software prototype for log generation, which takes as input a declarative or structured workflow model and emits logs containing positive and negative traces. The approach provides both a highly expressive notation for the description of the business model and the ability to generate logs with various customizable features. The final comparative study of other existing log generators reveals several advantages of the proposed approach and draws the direction of future improvements
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
VEGA-QSAR: AI inside a platform for predictive toxicology
No full textComputer simulation and predictive models are widely used in engineering, much less considered in life sciences. We present an initiative aimed to establish a dialogue within the community of scientists, regulators, industry representatives, offering a platform which combines the predictive capability of computer models, with some explanation tools, which may be convincing and helpful for human users to derive a conclusion. The resulting system covers a large set of toxicological endpoints
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