5,583 research outputs found
Using the event calculus for tracking the normative state of contracts
In this work, we have been principally concerned with the representation of contracts so that their normative state may be tracked in an automated fashion over their deployment lifetime. The normative state of a contract, at a particular time, is the aggregation of instances of normative relations that hold between contract parties at that time, plus the current values of contract variables. The effects of contract events on the normative state of a contract are specified using an XML formalisation of the Event Calculus, called ecXML. We use an example mail service agreement from the domain of web services to ground the discussion of our work. We give a characterisation of the agreement according to the normative concepts of: obligation, power and permission, and show how the ecXML representation may be used to track the state of the agreement, according to a narrative of contract events. We also give a description of a state tracking architecture, and a contract deployment tool, both of which have been implemented in the course of our work.
Online Handbook of Argumentation for AI: Volume 1
This volume contains revised versions of the papers selected for the first
volume of the Online Handbook of Argumentation for AI (OHAAI). Previously,
formal theories of argument and argument interaction have been proposed and
studied, and this has led to the more recent study of computational models of
argument. Argumentation, as a field within artificial intelligence (AI), is
highly relevant for researchers interested in symbolic representations of
knowledge and defeasible reasoning. The purpose of this handbook is to provide
an open access and curated anthology for the argumentation research community.
OHAAI is designed to serve as a research hub to keep track of the latest and
upcoming PhD-driven research on the theory and application of argumentation in
all areas related to AI.Comment: editor: Federico Castagna and Francesca Mosca and Jack Mumford and
Stefan Sarkadi and Andreas Xydi
Context-Aware Multi-Agent Planning in intelligent environments
A system is context-aware if it can extract, interpret and use context information and adapt its functionality to the current context of use. Multi-agent planning generalizes the problem of planning in domains where several agents plan and act together, and share resources, activities, and goals. This contribution presents a practical extension of a formal theoretical model for Context-Aware Multi-Agent Planning based upon an argumentationbased defeasible logic. Our framework, named CAMAP, is implemented on a platform for open multiagent systems and has been experimentally tested, among others, in applications of ambient intelligence in the field of health-care. CAMAP is based on a multi-agent
partial-order planning paradigm in which agents have diverse abilities, use an argumentation-based defeasible contextual reasoning to support their own beliefs and refute the beliefs of the others according to their context knowledge during the plan search process. CAMAP shows to be an adequate approach to tackle ambient intelligence problems as it gathers together in a single framework the ability of planning while it allows agents to put forward arguments that support or argue upon the accuracy, unambiguity and reliability of the context-aware information.This work is mainly supported by the Spanish Ministry of Science and Education under the FPU Grant Reference AP2009-1896 awarded to Sergio Pajares Ferrando, and Projects, TIN2011-27652-C03-01, and Consolider Ingenio 2010 CSD2007-00022.Pajares Ferrando, S.; Onaindia De La Rivaherrera, E. (2013). Context-Aware Multi-Agent Planning in intelligent environments. Information Sciences. 227:22-42. https://doi.org/10.1016/j.ins.2012.11.021S224222
Meta-level argumentation framework for representing and reasoning about disagreement
The contribution of this thesis is to the field of Artificial Intelligence (AI), specifically
to the sub-field called knowledge engineering. Knowledge engineering involves the
computer representation and use of the knowledge and opinions of human experts.In real world controversies, disagreements can be treated as opportunities for
exploring the beliefs and reasoning of experts via a process called argumentation.
The central claim of this thesis is that a formal computer-based framework for
argumentation is a useful solution to the problem of representing and reasoning with
multiple conflicting viewpoints.The problem which this thesis addresses is how to represent arguments in domains in
which there is controversy and disagreement between many relevant points of view.
The reason that this is a problem is that most knowledge based systems are founded in
logics, such as first order predicate logic, in which inconsistencies must be eliminated
from a
theory in order for meaningful inference to be possible from it.I argue that it is possible to devise an argumentation framework by describing one
(FORA : Framework for Opposition and Reasoning about Arguments). FORA
contains a language for representing the views of multiple experts who disagree or
have differing opinions. FORA also contains a suite of software tools which can
facilitate debate, exploration of multiple viewpoints, and construction and revision of
knowledge bases which are challenged by opposing opinions or evidence.A fundamental part of this thesis is the claim that arguments are meta-level structures
which describe the relationships between statements contained in knowledge bases. It
is important to make a clear distinction between representations in knowledge bases
(the object-level) and representations of the arguments implicit in knowledge bases
(the meta-level). FORA has been developed to make this distinction clear and its main
benefit is that the argument representations are independent of the object-level
representation language. This is useful because it facilitates integration of arguments
from multiple sources using different representation languages, and because it enables
knowledge engineering decisions to be made about how to structure arguments and
chains of reasoning, independently of object-level representation decisions.I argue that abstract argument representations are useful because they can facilitate a
variety of knowledge engineering tasks. These include knowledge acquisition;
automatic abstraction from existing formal knowledge bases; and construction, rerepresentation,
evaluation and criticism of object-level knowledge bases. Examples
of software tools contained within FORA are used to illustrate these uses of
argumentation structures. The utility of a meta-level framework for argumentation,
and FORA in particular, is demonstrated in terms of an important real world
controversy concerning the health risks of a group of toxic compounds called
aflatoxins
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