200,379 research outputs found
A note on knowledge-based programs and specifications
Knowledge-based program are programs with explicit tests for knowledge. They
have been used successfully in a number of applications. Sanders has pointed
out what seem to be a counterintuitive property of knowledge-based programs.
Roughly speaking, they do not satisfy a certain monotonicity property, while
standard programs (ones without tests for knowledge) do. It is shown that there
are two ways of defining the monotonicity property, which agree for standard
programs. Knowledge-based programs satisfy the first, but do not satisfy the
second. It is further argued by example that the fact that they do not satisfy
the second is actually a feature, not a problem. Moreover, once we allow the
more general class of knowledge-based specifications, standard programs do not
satisfy the monotonicity property either.Comment: To appear, Distributed Computin
From Uncertainty Data to Robust Policies for Temporal Logic Planning
We consider the problem of synthesizing robust disturbance feedback policies
for systems performing complex tasks. We formulate the tasks as linear temporal
logic specifications and encode them into an optimization framework via
mixed-integer constraints. Both the system dynamics and the specifications are
known but affected by uncertainty. The distribution of the uncertainty is
unknown, however realizations can be obtained. We introduce a data-driven
approach where the constraints are fulfilled for a set of realizations and
provide probabilistic generalization guarantees as a function of the number of
considered realizations. We use separate chance constraints for the
satisfaction of the specification and operational constraints. This allows us
to quantify their violation probabilities independently. We compute disturbance
feedback policies as solutions of mixed-integer linear or quadratic
optimization problems. By using feedback we can exploit information of past
realizations and provide feasibility for a wider range of situations compared
to static input sequences. We demonstrate the proposed method on two robust
motion-planning case studies for autonomous driving
Verification of Agent-Based Artifact Systems
Artifact systems are a novel paradigm for specifying and implementing
business processes described in terms of interacting modules called artifacts.
Artifacts consist of data and lifecycles, accounting respectively for the
relational structure of the artifacts' states and their possible evolutions
over time. In this paper we put forward artifact-centric multi-agent systems, a
novel formalisation of artifact systems in the context of multi-agent systems
operating on them. Differently from the usual process-based models of services,
the semantics we give explicitly accounts for the data structures on which
artifact systems are defined. We study the model checking problem for
artifact-centric multi-agent systems against specifications written in a
quantified version of temporal-epistemic logic expressing the knowledge of the
agents in the exchange. We begin by noting that the problem is undecidable in
general. We then identify two noteworthy restrictions, one syntactical and one
semantical, that enable us to find bisimilar finite abstractions and therefore
reduce the model checking problem to the instance on finite models. Under these
assumptions we show that the model checking problem for these systems is
EXPSPACE-complete. We then introduce artifact-centric programs, compact and
declarative representations of the programs governing both the artifact system
and the agents. We show that, while these in principle generate infinite-state
systems, under natural conditions their verification problem can be solved on
finite abstractions that can be effectively computed from the programs. Finally
we exemplify the theoretical results of the paper through a mainstream
procurement scenario from the artifact systems literature
The place of expert systems in a typology of information systems
This article considers definitions and claims of Expert Systems ( ES) and analyzes them in view of traditional Information systems (IS). It is argued that the valid specifications for ES do not differ fran those for IS. Consequently the theoretical study and the practical development of ES should not be a monodiscipline. Integration of ES development in classical mathematics and computer science opens the door to existing knowledge and experience. Aspects of existing ES are reviewed from this interdisciplinary point of view
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