Temat: Multi-agent systems - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Fine tuning of agent-based evolutionary computing
Autorzy:: Mizera, Michal
Nowotarski, Pawel
Byrski, Aleksander
Kisiel-Dorohinicki, Marek
Powiązania:: https://bibliotekanauki.pl/articles/91820.pdf
Data publikacji:: 2019
Wydawca:: Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:: multi-agent systems
metaheuristics
evolutionary computing
Opis:: Evolutionary Multi-agent System introduced by late Krzysztof Cetnarowicz and developed further at the AGH University of Science and Technology became a reliable optimization system, both proven experimentally and theoretically. This paper follows a work of Byrski further testing and analyzing the efficacy of this metaheuristic based on popular, high-dimensional benchmark functions. The contents of this paper will be useful for anybody willing to apply this computing algorithm to continuous and not only optimization.
Źródło:: Journal of Artificial Intelligence and Soft Computing Research; 2019, 9, 2; 81-97
2083-2567
2449-6499
Pojawia się w:: Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:: Biblioteka Nauki

Artykuł

Zmień widok

na półce

Skocz do pozycji: 2.

Tytuł:: Multi agent deep learning with cooperative communication
Autorzy:: Simões, David
Lau, Nuno
Reis, Luís Paulo
Powiązania:: https://bibliotekanauki.pl/articles/1837537.pdf
Data publikacji:: 2020
Wydawca:: Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:: multi-agent systems
deep reinforcement learning
centralized learning
Opis:: We consider the problem of multi agents cooperating in a partially-observable environment. Agents must learn to coordinate and share relevant information to solve the tasks successfully. This article describes Asynchronous Advantage Actor-Critic with Communication (A3C2), an end-to-end differentiable approach where agents learn policies and communication protocols simultaneously. A3C2 uses a centralized learning, distributed execution paradigm, supports independent agents, dynamic team sizes, partiallyobservable environments, and noisy communications. We compare and show that A3C2 outperforms other state-of-the-art proposals in multiple environments.
Źródło:: Journal of Artificial Intelligence and Soft Computing Research; 2020, 10, 3; 189-207
2083-2567
2449-6499
Pojawia się w:: Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:: Biblioteka Nauki

Artykuł

Zmień widok

na półce

Skocz do pozycji: 3.

Tytuł:: Nonlinear convergence algorithm: structural properties with doubly stochastic quadratic operators for multi-agent systems
Autorzy:: Abdulghafor, R.
Turaev, S.
Zeki, A.
Abubaker, A.
Powiązania:: https://bibliotekanauki.pl/articles/91876.pdf
Data publikacji:: 2018
Wydawca:: Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:: doubly stochastic quadratic operators
nonlinear convergence algorithm
consensus problem
multi-agent systems
kwadratowe operatory podwójnie stochastyczne
problem konsensusu
systemy wieloagentowe
Opis:: This paper proposes nonlinear operator of extreme doubly stochastic quadratic operator (EDSQO) for convergence algorithm aimed at solving consensus problem (CP) of discrete-time for multi-agent systems (MAS) on n-dimensional simplex. The first part undertakes systematic review of consensus problems. Convergence was generated via extreme doubly stochastic quadratic operators (EDSQOs) in the other part. However, this work was able to formulate convergence algorithms from doubly stochastic matrices, majorization theory, graph theory and stochastic analysis. We develop two algorithms: 1) the nonlinear algorithm of extreme doubly stochastic quadratic operator (NLAEDSQO) to generate all the convergent EDSQOs and 2) the nonlinear convergence algorithm (NLCA) of EDSQOs to investigate the optimal consensus for MAS. Experimental evaluation on convergent of EDSQOs yielded an optimal consensus for MAS. Comparative analysis with the convergence of EDSQOs and DeGroot model were carried out. The comparison was based on the complexity of operators, number of iterations to converge and the time required for convergences. This research proposed algorithm on convergence which is faster than the DeGroot linear model.
Źródło:: Journal of Artificial Intelligence and Soft Computing Research; 2018, 8, 1; 49-61
2083-2567
2449-6499
Pojawia się w:: Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:: Biblioteka Nauki

Artykuł

Zmień widok

na półce

Skocz do pozycji: 4.

Tytuł:: A layered multiagent decision support system for crisis management
Autorzy:: Kebair, F.
Powiązania:: https://bibliotekanauki.pl/articles/91749.pdf
Data publikacji:: 2012
Wydawca:: Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:: decision support systems
DSS
case of crisis
multi-agent
RoboCupRescue simulation system
Opis:: Decision Support Systems are powerful tools to help support making decisions. However, they are known to be customized for a specific purpose and can rarely be reused. Moreover, they do not support complex situations sufficiently. Our work addresses this challenge and consists in building a DSS that aims to help emergency managers to manage cases of crisis. The DSS is designed to be flexible and adaptive, so that it may be applied on different subjects of studies and whose behaviour may change with the change of its environment. We endowed it therefore with a multiagent layered core whose role is to represent dynamically and in real time the current situation, to characterize it and to compare it with past known scenarios. The final result of the DSS will help decision-makers to analyze the current crisis and its possible evolution. The RoboCupRescue simulation system is chosen as a test bed to illustrate and to test this approach.
Źródło:: Journal of Artificial Intelligence and Soft Computing Research; 2012, 2, 2; 125-132
2083-2567
2449-6499
Pojawia się w:: Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:: Biblioteka Nauki

Artykuł

Zmień widok

na półce

Informacja

Wyszukujesz frazę "Multi-agent systems" wg kryterium: Temat

Źródło danych

Dostawca treści

Kolekcja

Rok wydania

Wydawca

Temat

Autor

Typ dokumentu

Język