@conference {102,
	title = {A Flexible Dissimilarity Measure for Active and Passive 3D Structures and Its Application in the Fitness{\textendash}Distance Analysis},
	booktitle = {Applications of Evolutionary Computation},
	year = {2019},
	publisher = {Springer},
	organization = {Springer},
	abstract = {Evolutionary design of 3D structures {\textendash} either static structures, or equipped with some sort of a control system {\textendash} is one of the hardest optimization tasks. One of the reasons are rugged fitness landscapes resulting from complex and non-obvious genetic representations of such structures and their genetic operators. This paper investigates global convexity of fitness landscapes in optimization tasks of maximizing velocity and height of both active and passive structures. For this purpose, a new dissimilarity measure for 3D active and passive structures represented as undirected graphs is introduced. The proposed measure is general and flexible {\textendash} any vertex properties can be easily incorporated as dissimilarity components. The new measure was compared against the previously introduced measure in terms of triangle inequality satisfiability, changes in raw measure values and the computational cost. The comparison revealed improvements for triangle inequality and raw values at the expense of increased computational complexity. The investigation of global convexity of the fitness landscape, involving the fitness{\textendash}distance correlation analysis, revealed negative correlation between the dissimilarity of the structures and their fitness for most of the investigated cases.},
	isbn = {978-3-030-16692-2},
	doi = {10.1007/978-3-030-16692-2_8},
	url = {http://www.framsticks.com/files/common/DissimilarityMeasure3DStructuresFitnessDistance.pdf},
	author = {Komosinski, Maciej and Mensfelt, Agnieszka},
	editor = {Kaufmann, Paul and Castillo, Pedro A.}
}
@article {Chlebowski-et-al-2017,
	title = {Automated Generation of Erotetic Search Scenarios: Classification, Optimization, and Knowledge Extraction},
	journal = {ACM Transactions on Computational Logic},
	volume = {18},
	number = {2},
	year = {2017},
	pages = {8:1{\textendash}8:27},
	publisher = {ACM},
	address = {New York},
	abstract = {This paper concerns automated generation and processing of erotetic search scenarios (ESSs). ESSs are formal constructs characterized in Inferential Erotetic Logic that enable finding possible answers to a posed question by decomposing it into auxiliary questions. The first part of this work describes a formal account on ESSs. The formal approach is then applied to automatically generate ESSs, and the resulting scenarios are evaluated according to a number of criteria. These criteria are subjected to discordance analysis that reveals their mutual relationships. Finally, knowledge concerning relationships between different values of evaluation criteria is extracted by applying Apriori - an association rules mining algorithm. The proposed approach of integration of formal erotetic logic with computational tools provides an extensive insight into the former and helps with the development of efficient ESSs.},
	keywords = {knowledge extraction, Logic of questions, multicriteria analysis, optimal erotetic scenario, rule mining},
	issn = {1529-3785},
	doi = {10.1145/3056537},
	url = {http://www.cs.put.poznan.pl/mkomosinski/research/automated-erotetic-search-scenarios.pdf},
	author = {Chlebowski, Szymon and Maciej Komosinski and Adam Kups}
}
@inbook {Komosinski-et-al-2015,
	title = {Application of a morphological similarity measure to the analysis of shell morphogenesis in Foraminifera},
	booktitle = {Man{\textendash}Machine Interactions 4},
	series = {Advances in Intelligent Systems and Computing},
	volume = {391},
	year = {2016},
	pages = {215{\textendash}224},
	publisher = {Springer},
	organization = {Springer},
	abstract = {This work evaluates the genotype-to-phenotype mapping defined by one of the models of growth of foraminifera. Foraminifera are simple unicellular organisms with very diverse morphologies. To analyze the mapping, a morphological similarity measure is needed that compares 3D structures. One of the key components of the similarity estimation algorithm is Singular Value Decomposition (SVD). Since this algorithm is heavily used and its performance is important, four SVD implementations have been compared in this work. Distance matrices of the phenotypes obtained for equally distant genotypes were computed using the similarity measure. For the visualization of the phenotype space, multidimensional scaling techniques were used. Visual comparison of the genotype and the phenotype spaces revealed characteristics and potential weaknesses of the analyzed model of foraminifera growth, and demonstrated usefulness of the proposed approach.},
	isbn = {978-3-319-23436-6},
	doi = {10.1007/978-3-319-23437-3_18},
	url = {http://www.framsticks.com/files/common/ForaminiferaGenotypePhenotypeMapping.pdf},
	author = {Maciej Komosinski and Agnieszka Mensfelt and Pawe{\l} Topa and Jaros{\l}aw Tyszka},
	editor = {Gruca, Aleksandra and Brachman, Agnieszka and Kozielski, Stanis{\l}aw and Czach{\'o}rski, Tadeusz}
}
@inbook {107,
	title = {eVolutus: a configurable platform designed for ecological and evolutionary experiments tested on Foraminifera},
	booktitle = {Man{\textendash}Machine Interactions 4},
	series = {Advances in Intelligent Systems and Computing},
	volume = {391},
	year = {2016},
	pages = {269{\textendash}278},
	publisher = {Springer},
	organization = {Springer},
	isbn = {978-3-319-23436-6},
	doi = {10.1007/978-3-319-23437-3_23},
	url = {http://dx.doi.org/10.1007/978-3-319-23437-3_23},
	author = {Pawe{\l} Topa and Maciej Komosinski and Maciej Bassara and Jaros{\l}aw Tyszka},
	editor = {Gruca, Aleksandra and Brachman, Agnieszka and Kozielski, Stanis{\l}aw and Czach{\'o}rski, Tadeusz}
}
