125,075 research outputs found
Context-dependent Utilities
Savage's framework of subjective preference among acts provides a paradigmatic derivation of rational subjective probabilities within a more general theory of rational decisions. The system is based on a set of possible states of the world, and on acts, which are functions that assign to each state a consequence. The representation theorem states that the given preference between acts is determined by their expected utilities, based on uniquely determined probabilities (assigned to sets of states), and numeric utilities assigned to consequences. Savage's derivation, however, is based on a highly problematic well-known assumption not included among his postulates: for any consequence of an act in some state, there is a "constant act" which has that consequence in all states. This ability to transfer consequences from state to state is, in many cases, miraculous -- including simple scenarios suggested by Savage as natural cases for applying his theory. We propose a simplification of the system, which yields the representation theorem without the constant act assumption. We need only postulates P1-P6. This is done at the cost of reducing the set of acts included in the setup. The reduction excludes certain theoretical infinitary scenarios, but includes the scenarios that should be handled by a system that models human decisions
Typing Context-Dependent Behavioural Variation
Context Oriented Programming (COP) concerns the ability of programs to adapt
to changes in their running environment. A number of programming languages
endowed with COP constructs and features have been developed. However, some
foundational issues remain unclear. This paper proposes adopting static
analysis techniques to reason on and predict how programs adapt their
behaviour. We introduce a core functional language, ContextML, equipped with
COP primitives for manipulating contexts and for programming behavioural
variations. In particular, we specify the dispatching mechanism, used to select
the program fragments to be executed in the current active context. Besides the
dynamic semantics we present an annotated type system. It guarantees that the
well-typed programs adapt to any context, i.e. the dispatching mechanism always
succeeds at run-time.Comment: In Proceedings PLACES 2012, arXiv:1302.579
Context dependent learning in neural networks
In this paper an extension to the standard error backpropagation learning rule for multi-layer feed forward neural networks is proposed, that enables them to be trained for context dependent information. The context dependent learning is realised by using a different error function (called Average Risk: AVR) in stead of the sum of squared errors (SQE) normally used in error backpropagation and by adapting the update rules. It is shown that for applications where this context dependent information is important, a major improvement in performance is obtained
Context dependent revocation in delegated XACML
The XACML standard defines an XML based language for defining access control policies and a related processing model. Recent work aims to add delegation to XACML in order to express the right to administrate XACML policies within XACML itself. The delegation profile draft explains how to validate the right to issue a policy, but there are no provisions for removing a policy. This paper proposes a revocation model for delegated XACML. A novel feature of this model is that whether a revocation is valid or not, depends not only on who issued the revocation, but also on the context in which an attempt to use the revoked policy is done
Context-dependent feature analysis with random forests
In many cases, feature selection is often more complicated than identifying a
single subset of input variables that would together explain the output. There
may be interactions that depend on contextual information, i.e., variables that
reveal to be relevant only in some specific circumstances. In this setting, the
contribution of this paper is to extend the random forest variable importances
framework in order (i) to identify variables whose relevance is
context-dependent and (ii) to characterize as precisely as possible the effect
of contextual information on these variables. The usage and the relevance of
our framework for highlighting context-dependent variables is illustrated on
both artificial and real datasets.Comment: Accepted for presentation at UAI 201
Context-dependent Trust Decisions with Subjective Logic
A decision procedure implemented over a computational trust mechanism aims to
allow for decisions to be made regarding whether some entity or information
should be trusted. As recognised in the literature, trust is contextual, and we
describe how such a context often translates into a confidence level which
should be used to modify an underlying trust value. J{\o}sang's Subjective
Logic has long been used in the trust domain, and we show that its operators
are insufficient to address this problem. We therefore provide a
decision-making approach about trust which also considers the notion of
confidence (based on context) through the introduction of a new operator. In
particular, we introduce general requirements that must be respected when
combining trustworthiness and confidence degree, and demonstrate the soundness
of our new operator with respect to these properties.Comment: 19 pages, 4 figures, technical report of the University of Aberdeen
(preprint version
Probing context-dependent errors in quantum processors
Gates in error-prone quantum information processors are often modeled using
sets of one- and two-qubit process matrices, the standard model of quantum
errors. However, the results of quantum circuits on real processors often
depend on additional external "context" variables. Such contexts may include
the state of a spectator qubit, the time of data collection, or the temperature
of control electronics. In this article we demonstrate a suite of simple,
widely applicable, and statistically rigorous methods for detecting context
dependence in quantum circuit experiments. They can be used on any data that
comprise two or more "pools" of measurement results obtained by repeating the
same set of quantum circuits in different contexts. These tools may be
integrated seamlessly into standard quantum device characterization techniques,
like randomized benchmarking or tomography. We experimentally demonstrate these
methods by detecting and quantifying crosstalk and drift on the publicly
accessible 16-qubit ibmqx3.Comment: 11 pages, 3 figures, code and data available in source file
Specification and Verification of Context-dependent Services
Current approaches for the discovery, specification, and provision of
services ignore the relationship between the service contract and the
conditions in which the service can guarantee its contract. Moreover, they do
not use formal methods for specifying services, contracts, and compositions.
Without a formal basis it is not possible to justify through formal
verification the correctness conditions for service compositions and the
satisfaction of contractual obligations in service provisions. We remedy this
situation in this paper. We present a formal definition of services with
context-dependent contracts. We define a composition theory of services with
context-dependent contracts taking into consideration functional,
nonfunctional, legal and contextual information. Finally, we present a formal
verification approach that transforms the formal specification of service
composition into extended timed automata that can be verified using the model
checking tool UPPAAL.Comment: In Proceedings WWV 2011, arXiv:1108.208
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