@article {126,
	title = {Type A and Type B Effects, Time-Order Error and Weber{\textquoteright}s Law in Human Timing {\textendash} Simulations and Synthesis},
	year = {2021},
	institution = {Poznan University of Technology, Institute of Computing Science},
	abstract = {This article presents a computational approach to the theoretical integration of the psychophysical phenomena in human timing. While there are many useful models of human timing, analyses are scarce on how these models explain the relationships between several phenomena at the same time. The presented research is an attempt to primarily explain and integrate the time-order error with the Type A and Type B phenomena. The final result of this work also encompasses Weber{\textquoteright}s law property and relates it to the aforementioned order-related effects. The theoretical framework used is the Clock-Counter Timing Network (CCTN), an artificial neural network timing model which has been constructed to explain the process of comparing durations of stimuli. Extensive simulations performed with the use of this model revealed that the considered psychophysical properties may be strongly interrelated and dependent on a simple perceptual mechanism. The obtained results allow to formulate specific experimentally testable predictions.},
	issn = {RA{\textendash}2/2021},
	url = {http://www.framsticks.com/files/common/HumanTimingSimulation-TypeA-TypeB-TOE-WebersLaw.pdf},
	author = {Komosinski, Maciej and Kups, Adam}
}
@article {109,
	title = {Tournament-based convection selection in evolutionary algorithms},
	journal = {PPAM 2017 proceedings, Lecture Notes in Computer Science},
	year = {2018},
	abstract = {One of the problems that single-threaded (non-parallel) evolutionary algorithms encounter is premature convergence and the lack of diversity in the population. To counteract this problem and improve the performance of evolutionary algorithms in terms of the quality of optimized solutions, a new subpopulation-based selection scheme - the convection selection - is introduced and analyzed in this work. This new selection scheme is compared against traditional selection of individuals in a single-population evolutionary processes. The experimental results indicate that the use of subpopulations with fitness-based assignment of individuals yields better results than both random assignment and a traditional, non-parallel evolutionary architecture.},
	doi = {10.1007/978-3-319-78054-2_44},
	url = {http://www.framsticks.com/files/common/TournamentBasedConvectionSelectionEvolutionary.pdf},
	author = {Maciej Komosinski and Konrad Miazga}
}
@article {Komosinski-and-Kups-2015,
	title = {Time-order error and scalar variance in a computational model of human timing: simulations and predictions},
	journal = {Computational Cognitive Science},
	volume = {1},
	number = {3},
	year = {2015},
	pages = {1{\textendash}24},
	publisher = {Springer},
	abstract = {This work introduces a computational model of human temporal discrimination mechanism - the Clock-Counter Timing Network. It is an artificial neural network implementation of a timing mechanism based on the informational architecture of the popular Scalar Timing Model. The model has been simulated in a virtual environment enabling computational experiments which imitate a temporal discrimination task - the two-alternative forced choice task. The influence of key parameters of the model (including the internal pacemaker speed and the variability of memory translation) on the network accuracy and the time-order error phenomenon has been evaluated. The results of simulations reveal how activities of different modules contribute to the overall performance of the model. These results can be compared and verified in empirical experiments with human participants, especially when the modes of activity of the internal timing mechanism are changed because of some external conditions, or are impaired due to some kind of a neural degradation process.},
	doi = {10.1186/s40469-015-0002-0},
	url = {http://dx.doi.org/10.1186/s40469-015-0002-0},
	author = {Maciej Komosinski and Adam Kups}
}
@inbook {Komosinski-and-Kubiak-2001,
	title = {Taxonomy in {A}life. {M}easures of similarity for complex artificial organisms},
	booktitle = {Advances in Artificial Life. Lecture Notes in Artificial Intelligence 2159},
	year = {2001},
	pages = {685{\textendash}694},
	publisher = {Springer-Verlag},
	organization = {Springer-Verlag},
	keywords = {Agents, AL, Biology, EA, Simulation},
	url = {http://www.framsticks.com/files/common/Komosinski_TaxonomyAlife_ECAL2001.pdf}
}
