In this paper, a new machine learning algorithm for multi-agent systems is introduced. The algorithm is based on associative arrays, thus it becomes less complex and more efficient substitute of artificial neural networks and Bayesian networks, which is confirmed by performance measurements. Implementation of machine learning algorithm in multi-agent system for aided design of selected control systems allowed to improve the performance by reducing time of processing requests, that were previously acknowledged and stored in learning module. This article contains an insight into different machine learning algorithms and includes the classification of learning techniques regarding the criteria depicted by multi-agent systems. The publication is also an attempt to provide the answer for a question posted by Shoham, Powers and Grenager: “If multi-agent learning is the answer, what is the question?”
Autorzy
- mgr inż. Przemysław Spychalski,
- dr hab. inż. Ryszard Arendt link otwiera się w nowej karcie
Informacje dodatkowe
- DOI
- Cyfrowy identyfikator dokumentu elektronicznego link otwiera się w nowej karcie 10.1016/j.parco.2018.03.006
- Kategoria
- Publikacja w czasopiśmie
- Typ
- artykuł w czasopiśmie wyróżnionym w JCR
- Język
- angielski
- Rok wydania
- 2018
Źródło danych: MOSTWiedzy.pl - publikacja "Machine Learning in Multi-Agent Systems using Associative Arrays" link otwiera się w nowej karcie