26,622 research outputs found
Collaboration on reference to objects that are not mutually known
In conversation, a person sometimes has to refer to an object that is not
previously known to the other participant. We present a plan-based model of how
agents collaborate on reference of this sort. In making a reference, an agent
uses the most salient attributes of the referent. In understanding a reference,
an agent determines his confidence in its adequacy as a means of identifying
the referent. To collaborate, the agents use judgment, suggestion, and
elaboration moves to refashion an inadequate referring expression.Comment: 6 pages, to appear in proceedings of COLING-94, LaTeX (now uses
fullname.sty, fullname.bst
Agents and stream data mining: a new perspective
Many organizations struggle with the massive amount of data they collect. Today, data does more than serve as the ingredients for churning out statistical reports. They help support efficient operations in many organizations, and to some extent, data provide the competitive intelligence organizations need to survive in today\u27s economy. Data mining can\u27t always deliver timely and relevant results because data are constantly changing. However, stream-data processing might be more effective, judging by the Matrix project.<br /
Where creativity comes from: the social spaces of embodied minds
This paper explores creative design, social interaction and perception. It proposes that creativity at a social level is not a result of many individuals trying to be creative at a personal level, but occurs naturally in the social interaction between comparatively simple minds embodied in a complex world. Particle swarm algorithms can model group interaction in shared spaces, but design space is not necessarily one pre-defined space of set parameters on which everyone can agree, as individual minds are very different. A computational model is proposed that allows a similar swarm to occur between spaces of different description and even dimensionality. This paper explores creative design, social interaction and perception. It proposes that creativity at a social level is not a result of many individuals trying to be creative at a personal level, but occurs naturally in the social interaction between comparatively simple minds embodied in a complex world. Particle swarm algorithms can model group interaction in shared spaces, but design space is not necessarily one pre-defined space of set parameters on which everyone can agree, as individual minds are very different. A computational model is proposed that allows a similar swarm to occur between spaces of different description and even dimensionality
A framework for the definition of metrics for actor-dependency models
Actor-dependency models are a formalism aimed at providing intentional
descriptions of processes as a network of dependency relationships among
actors. This kind of models is currently widely used in the early phase of
requirements engineering as well as in other contexts such as organizational
analysis and business process reengineering. In this paper, we are
interested in the definition of a framework for the formulation of metrics
over these models. These metrics are used to analyse the models with respect
to some properties that are interesting for the system being modelled, such
as security, efficiency or accuracy. The metrics are defined in terms of the
actors and dependencies of the model. We distinguish three different kinds
of metrics that are formally defined, and then we apply the framework at two
different layers of a meeting scheduler system.Postprint (published version
Distributed Hybrid Simulation of the Internet of Things and Smart Territories
This paper deals with the use of hybrid simulation to build and compose
heterogeneous simulation scenarios that can be proficiently exploited to model
and represent the Internet of Things (IoT). Hybrid simulation is a methodology
that combines multiple modalities of modeling/simulation. Complex scenarios are
decomposed into simpler ones, each one being simulated through a specific
simulation strategy. All these simulation building blocks are then synchronized
and coordinated. This simulation methodology is an ideal one to represent IoT
setups, which are usually very demanding, due to the heterogeneity of possible
scenarios arising from the massive deployment of an enormous amount of sensors
and devices. We present a use case concerned with the distributed simulation of
smart territories, a novel view of decentralized geographical spaces that,
thanks to the use of IoT, builds ICT services to manage resources in a way that
is sustainable and not harmful to the environment. Three different simulation
models are combined together, namely, an adaptive agent-based parallel and
distributed simulator, an OMNeT++ based discrete event simulator and a
script-language simulator based on MATLAB. Results from a performance analysis
confirm the viability of using hybrid simulation to model complex IoT
scenarios.Comment: arXiv admin note: substantial text overlap with arXiv:1605.0487
Modelling and analyzing adaptive self-assembling strategies with Maude
Building adaptive systems with predictable emergent behavior is a challenging task and it is becoming a critical need. The research community has accepted the challenge by introducing approaches of various nature: from software architectures, to programming paradigms, to analysis techniques. We recently proposed a conceptual framework for adaptation centered around the role of control data. In this paper we show that it can be naturally realized in a reflective logical language like Maude by using the Reflective Russian Dolls model. Moreover, we exploit this model to specify, validate and analyse a prominent example of adaptive system: robot swarms equipped with self-assembly strategies. The analysis exploits the statistical model checker PVeStA
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