99,794 research outputs found
Knowledge revision in systems based on an informed tree search strategy : application to cartographic generalisation
Many real world problems can be expressed as optimisation problems. Solving
this kind of problems means to find, among all possible solutions, the one that
maximises an evaluation function. One approach to solve this kind of problem is
to use an informed search strategy. The principle of this kind of strategy is
to use problem-specific knowledge beyond the definition of the problem itself
to find solutions more efficiently than with an uninformed strategy. This kind
of strategy demands to define problem-specific knowledge (heuristics). The
efficiency and the effectiveness of systems based on it directly depend on the
used knowledge quality. Unfortunately, acquiring and maintaining such knowledge
can be fastidious. The objective of the work presented in this paper is to
propose an automatic knowledge revision approach for systems based on an
informed tree search strategy. Our approach consists in analysing the system
execution logs and revising knowledge based on these logs by modelling the
revision problem as a knowledge space exploration problem. We present an
experiment we carried out in an application domain where informed search
strategies are often used: cartographic generalisation.Comment: Knowledge Revision; Problem Solving; Informed Tree Search Strategy;
Cartographic Generalisation., Paris : France (2008
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Detecting and correcting errors in ruled-based expert systems : an integration of empirical and explanation-based learning
In this paper, we argue that techniques proposed for combining empirical and explanation-based learning methods can also be used to detect errors in rule-based expert systems, to isolate the blame for these errors to a small number of rules and suggest revisions to the rules to eliminate these errors. We demonstrate that FOCL, an extension to Quinlan's FOIL program, can learn in spite of an incorrect domain theory (e.g., a knowledge base of an expert system that contains some erroneous rules). A prototype knowledge acquisition tool, KR-FOCL, has been constructed that can utilize a trace of FOCL to suggest revisions to a rule base
Beliefs and Conflicts in a Real World Multiagent System
In a real world multiagent system, where the
agents are faced with partial, incomplete and
intrinsically dynamic knowledge, conflicts are
inevitable. Frequently, different agents have
goals or beliefs that cannot hold simultaneously.
Conflict resolution methodologies have to be
adopted to overcome such undesirable occurrences.
In this paper we investigate the application of
distributed belief revision techniques as the support
for conflict resolution in the analysis of the
validity of the candidate beams to be produced
in the CERN particle accelerators.
This CERN multiagent system contains a higher
hierarchy agent, the Specialist agent, which
makes use of meta-knowledge (on how the conflicting
beliefs have been produced by the other
agents) in order to detect which beliefs should be
abandoned. Upon solving a conflict, the Specialist
instructs the involved agents to revise their
beliefs accordingly.
Conflicts in the problem domain are mapped into
conflicting beliefs of the distributed belief revision
system, where they can be handled by
proven formal methods. This technique builds
on well established concepts and combines them
in a new way to solve important problems. We
find this approach generally applicable in several
domains
A Survey on IT-Techniques for a Dynamic Emergency Management in Large Infrastructures
This deliverable is a survey on the IT techniques that are relevant to the three use cases of the project EMILI. It describes the state-of-the-art in four complementary IT areas: Data cleansing, supervisory control and data acquisition, wireless sensor networks and complex event processing. Even though the deliverable’s authors have tried to avoid a too technical language and have tried to explain every concept referred to, the deliverable might seem rather technical to readers so far little familiar with the techniques it describes
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