193,454 research outputs found
Inference Rules in some temporal multi-epistemic propositional logics
Multi-modal logics are among the best tools developed so far to analyse
human reasoning and agents’ interactions. Recently multi-modal
logics have found several applications in Artificial Intelligence (AI) and
Computer Science (CS) in the attempt to formalise reasoning about
the behavior of programs. Modal logics deal with sentences that are
qualified by modalities. A modality is any word that could be added to
a statement p to modify its mode of truth. Temporal logics are obtained
by joining tense operators to the classical propositional calculus, giving
rise to a language very effective to describe the flow of time. Epistemic
logics are suitable to formalize reasoning about agents possessing a
certain knowledge. Combinations of temporal and epistemic logics are
particularly effective in describing the interaction of agents through the
flow of time. Although not yet fully investigated, this approach has
found many fruitful applications. These are concerned with the development
of systems modelling reasoning about knowledge and space,
reasoning under uncertainty, multi-agent reasoning et c.
Despite their power, multi modal languages cannot handle a changing
environment. But this is exactly what is required in the case of human
reasoning, computation and multi-agent environment. For this purpose,
inference rules are a core instrument. So far, the research in this
field has investigated many modal and superintuitionistic logics. However,
for the case of multi-modal logics, not much is known concerning
admissible inference rules.
In our research we extend the investigation to some multi-modal propositional logics which combine tense and knowledge modalities. As far
as we are concerned, these systems have never been investigated before.
In particular we start by defining our systems semantically; further we
prove such systems to enjoy the effective finite model property and to
be decidable with respect to their admissible inference rules. We turn
then our attention to the syntactical side and we provide sound and
complete axiomatic systems. We conclude our dissertation by introducing
the reader to the piece of research we are currently working on.
Our original results can be found in [9, 4, 11] (see Appendix A). They
have also been presented by the author at some international conferences
and schools (see [8, 10, 5, 7, 6] and refer to Appendix B for more
details).
Our project concerns philosophy, mathematics, AI and CS. Modern
applications of logic in CS and AI often require languages able to represent
knowledge about dynamic systems. Multi-modal logics serve
these applications in a very efficient way, and we would absorb and
develop some of these techniques to represent logical consequences in
artificial intelligence and computation
A survey of agent-oriented methodologies
This article introduces the current agent-oriented methodologies. It discusses what approaches have been followed (mainly extending existing object oriented and knowledge engineering methodologies), the suitability of these approaches for agent modelling, and some conclusions drawn from the survey
Coordination approaches and systems - part I : a strategic perspective
This is the first part of a two-part paper presenting a fundamental review and summary of research of design coordination and cooperation technologies. The theme of this review is aimed at the research conducted within the decision management aspect of design coordination. The focus is therefore on the strategies involved in making decisions and how these strategies are used to satisfy design requirements. The paper reviews research within collaborative and coordinated design, project and workflow management, and, task and organization models. The research reviewed has attempted to identify fundamental coordination mechanisms from different domains, however it is concluded that domain independent mechanisms need to be augmented with domain specific mechanisms to facilitate coordination. Part II is a review of design coordination from an operational perspective
MACS: Multi-agent COTR system for Defense Contracting
The field of intelligent multi-agent systems has expanded rapidly in the recent past. Multi-agent architectures and systems are being investigated and continue to develop. To date, little has been accomplished in applying multi-agent systems to the defense acquisition domain. This paper describes the design, development, and related considerations of a multi-agent system in the area of procurement and contracting for the defense acquisition community
Multi-agent systems for power engineering applications - part 1 : Concepts, approaches and technical challenges
This is the first part of a 2-part paper that has arisen from the work of the IEEE Power Engineering Society's Multi-Agent Systems (MAS) Working Group. Part 1 of the paper examines the potential value of MAS technology to the power industry. In terms of contribution, it describes fundamental concepts and approaches within the field of multi-agent systems that are appropriate to power engineering applications. As well as presenting a comprehensive review of the meaningful power engineering applications for which MAS are being investigated, it also defines the technical issues which must be addressed in order to accelerate and facilitate the uptake of the technology within the power and energy sector. Part 2 of the paper explores the decisions inherent in engineering multi-agent systems for applications in the power and energy sector and offers guidance and recommendations on how MAS can be designed and implemented
Artificial Intelligence in the Context of Human Consciousness
Artificial intelligence (AI) can be defined as the ability of a machine to learn and make decisions based on acquired information. AI’s development has incited rampant public speculation regarding the singularity theory: a futuristic phase in which intelligent machines are capable of creating increasingly intelligent systems. Its implications, combined with the close relationship between humanity and their machines, make achieving understanding both natural and artificial intelligence imperative. Researchers are continuing to discover natural processes responsible for essential human skills like decision-making, understanding language, and performing multiple processes simultaneously. Artificial intelligence attempts to simulate these functions through techniques like artificial neural networks, Markov Decision Processes, Human Language Technology, and Multi-Agent Systems, which rely upon a combination of mathematical models and hardware
Overview on agent-based social modelling and the use of formal languages
Transdisciplinary Models and Applications investigates a variety of programming languages used in validating and verifying models in order to assist in their eventual implementation. This book will explore different methods of evaluating and formalizing simulation models, enabling computer and industrial engineers, mathematicians, and students working with computer simulations to thoroughly understand the progression from simulation to product, improving the overall effectiveness of modeling systems.Postprint (author's final draft
Integrating an agent-based wireless sensor network within an existing multi-agent condition monitoring system
The use of wireless sensor networks for condition monitoring is gaining ground across all sectors of industry, and while their use for power engineering applications has yet been limited, they represent a viable platform for next-generation substation condition monitoring systems. For engineers to fully benefit from this new approach to condition monitoring, new sensor data must be incorporated into a single integrated system. This paper proposes the integration of an agent-based wireless sensor network with an existing agent-based condition monitoring system. It demonstrates that multi-agent systems can be extended down to the sensor level while considering the reduced energy availability of low-power embedded devices. A novel agent-based approach to data translation is presented, which is demonstrated through two case studies: a lab-based temperature and vibration monitoring system, and a proposal to integrate a wireless sensor network to an existing technology demonstrator deployed in a substation in the UK
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