32,444 research outputs found
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
Beliefs and Conflicts in a Real World Multi-Agent 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 con-
flicting 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
Belief Revision in Multi-Agent Systems
The ability to respond sensibly to changing and conflicting beliefs
is an integral part of intelligent agency. To this end, we outline the design and
implementation of a Distributed Assumption-based Truth Maintenance System
(DATMS) appropriate for controlling cooperative problem solving in a
dynamic real world multi-agent community. Our DATMS works on the principle
of local coherence which means that different agents can have different
perspectives on the same fact provided that these stances are appropriately
justified. The belief revision algorithm is presented, the meta-level code
needed to ensure that all system-wide queries can be uniquely answered is
described, and the DATMS’ implementation in a general purpose multi-agent
shell is discussed
Detection and resolution of normative conflicts in multi-agent systems : a literature survey
Peer reviewedPostprin
Distributed Belief Revision and Environmental Decision Support
This article discusses the development of an Intelligent Distributed Environmental
Decision Support System, built upon the association of a Multi-agent Belief
Revision System with a Geographical Information System (GIS). The inherent
multidisciplinary features of the involved expertises in the field of environmental
management, the need to define clear policies that allow the synthesis of divergent
perspectives, its systematic application, and the reduction of the costs and
time that result from this integration, are the main reasons that motivate the proposal
of this project.
This paper is organised in two parts: in the first part we present and discuss the
developed - Distributed Belief Revision Test-bed - DiBeRT; in the second part we
analyse its application to the environmental decision support domain, with special
emphasis on the interface with a GIS
An comparative analysis of different models of belief revision using information from multiple sources
In this work we analyze the problem of knowledge representation in a collaborative multi-agent system where agents can obtain new information from others through communication. Namely, we analyze several approaches of belief revision in multi-agent systems. We will describe different research lines in this topic and we will focus on Belief Revision using Information from Multiple Sources. For this, we are going to accomplish a comparative analysis of different models of belief revision that use information from multiple sources.Workshop de Agentes y Sistemas Inteligentes (WASI)Red de Universidades con Carreras en Informática (RedUNCI
Logic, self-awareness and self-improvement: The metacognitive loop and the problem of brittleness
This essay describes a general approach to building perturbation-tolerant autonomous systems, based on the conviction that artificial agents should be able notice when something is amiss, assess the anomaly, and guide a solution into place. We call this basic strategy of self-guided learning the metacognitive loop; it involves the system monitoring, reasoning about, and, when necessary, altering its own decision-making components. In this essay, we (a) argue that equipping agents with a metacognitive loop can help to overcome the brittleness problem, (b) detail the metacognitive loop and its relation to our ongoing work on time-sensitive commonsense reasoning, (c) describe specific, implemented systems whose perturbation tolerance was improved by adding a metacognitive loop, and (d) outline both short-term and long-term research agendas
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