Pełnotekstowe zasoby PLDML oraz innych baz dziedzinowych są już dostępne w nowej Bibliotece Nauki.
Zapraszamy na https://bibliotekanauki.pl
Preferencje help
Polish version English version Język
Widoczny [Schowaj] Abstrakt
Liczba wyników

Znaleziono wyników: 3

Liczba wyników na stronie
first rewind previous Strona / 1 next fast forward last

Wyniki wyszukiwania

Wyszukiwano:
w słowach kluczowych:  multi-agent system
help Sortuj według:

help Ogranicz wyniki do:
first rewind previous Strona / 1 next fast forward last
1
Content available remote

FSP and FLTL framework for specification and verification of middle-agents

100%
Bădică A., Bădică C.
International Journal of Applied Mathematics and Computer Science
|
2011
|
tom 21
|
nr 1
9-25
EN
Agents are a useful abstraction frequently employed as a basic building block in modeling service, information and resource sharing in global environments. The connecting of requester with provider agents requires the use of specialized agents known as middle-agents. In this paper, we propose a formal framework intended to precisely characterize types of middle-agents with a special focus on matchmakers, brokers and front-agents by formally modeling their interactions with requesters and providers. Our approach is based on capturing interaction protocols between requesters, providers and middle-agents as finite state processes represented using FSP process algebra. The resulting specifications are formally verifiable using FLTL temporal logic. The main results of this work include (i) precise specification of interaction protocols depending on the type of middle-agent (this can also be a basis for characterizing types of middle-agents), (ii) improvement of communication between designers and developers and facilitation of formal verification of agent systems, (iii) guided design and implementation of agent-based software systems that incorporate middle-agents.
2
Artykuł dostępny w postaci pełnego tekstu - kliknij by otworzyć plik
Content available

A belief revision approach for argumentation-based negotiation agents

100%
Pilotti P., Casali A., Chesñevar C.
International Journal of Applied Mathematics and Computer Science
|
2015
|
tom 25
|
nr 3
455-470
EN
Negotiation is an interaction that happens in multi-agent systems when agents have conflicting objectives and must look for an acceptable agreement. A typical negotiating situation involves two agents that cannot reach their goals by themselves because they do not have some resources they need or they do not know how to use them to reach their goals. Therefore, they must start a negotiation dialogue, taking also into account that they might have incomplete or wrong beliefs about the other agent's goals and resources. This article presents a negotiating agent model based on argumentation, which is used by the agents to reason on how to exchange resources and knowledge in order to achieve their goals. Agents that negotiate have incomplete beliefs about the others, so that the exchange of arguments gives them information that makes it possible to update their beliefs. In order to formalize their proposals in a negotiation setting, the agents must be able to generate, select and evaluate arguments associated with such offers, updating their mental state accordingly. In our approach, we will focus on an argumentation-based negotiation model between two cooperative agents. The arguments generation and interpretation process is based on belief change operations (expansions, contractions and revisions), and the selection process is a based on a strategy. This approach is presented through a high-level algorithm implemented in logic programming. We show various theoretical properties associated with this approach, which have been formalized and proved using Coq, a formal proof management system. We also illustrate, through a case study, the applicability of our approach in order to solve a slightly modified version of the well-known home improvement agents problem. Moreover, we present various simulations that allow assessing the impact of belief revision on the negotiation process.
3
Content available remote

Application of agent-based simulated annealing and tabu search procedures to solving the data reduction problem

88%
Czarnowski I., Jędrzejowicz P.
International Journal of Applied Mathematics and Computer Science
|
2011
|
tom 21
|
nr 1
57-68
EN
The problem considered concerns data reduction for machine learning. Data reduction aims at deciding which features and instances from the training set should be retained for further use during the learning process. Data reduction results in increased capabilities and generalization properties of the learning model and a shorter time of the learning process. It can also help in scaling up to large data sources. The paper proposes an agent-based data reduction approach with the learning process executed by a team of agents (A-Team). Several A-Team architectures with agents executing the simulated annealing and tabu search procedures are proposed and investigated. The paper includes a detailed description of the proposed approach and discusses the results of a validating experiment.
first rewind previous Strona / 1 next fast forward last
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.