30 citations · 55 across the 5 of their papers we have counts for
5 papers
Socio-cognitive agent-oriented evolutionary algorithm with trust-based optimization
Aleksandra Urbańczyk, Krzysztof Czech, Piotr Urbańczyk +2
This paper introduces the Trust-Based Optimization (TBO), a novel extension of the island model in evolutionary computation that replaces conventional periodic migrations with a fl…
Applying Autonomous Hybrid Agent-based Computing to Difficult Optimization Problems
Mateusz Godzik, Jacek Dajda, Marek Kisiel-Dorohinicki +5
Evolutionary multi-agent systems (EMASs) are very good at dealing with difficult, multi-dimensional problems, their efficacy was proven theoretically based on analysis of the relev…
Socio-cognitive Optimization of Time-delay Control Problems using Evolutionary Metaheuristics
Piotr Kipinski, Hubert Guzowski, Aleksandra Urbanczyk +8
Metaheuristics are universal optimization algorithms which should be used for solving difficult problems, unsolvable by classic approaches. In this paper we aim at constructing nov…
Massively-concurrent Agent-based Evolutionary Computing
D. Krzywicki, W. Turek, A. Byrski +1
The fusion of the multi-agent paradigm with evolutionary computation yielded promising results in many optimization problems. Evolutionary multi-agent system (EMAS) are more simila…
Computing Agents for Decision Support Systems
D. Krzywicki, Ł. Faber, A. Byrski +1
In decision support systems, it is essential to get a candidate solution fast, even if it means resorting to an approximation. This constraint introduces a scalability requirement…