@conference {2579,
	title = {Late Bloomers, First Glances, Second Chances: Exploration of the Mechanisms Behind Fitness Diversity},
	booktitle = {Genetic and Evolutionary Computation Conference (GECCO {\textquoteright}24)},
	year = {2024},
	publisher = {ACM},
	organization = {ACM},
	abstract = {Fitness diversity is an idea in the field of evolutionary algorithms, which calls for supporting the evolution of solutions at all fitness levels simultaneously. In some cases, this idea may even extend to cultivating the worst solutions. While this may seem counterintuitive, fitness diversity has shown its promise in algorithms such as Hierarchical Fair Competition and Convection Selection. Although these algorithms share many similarities, the role fitness diversity serves in each of them is different. In Hierarchical Fair Competition, fitness diversity facilitates a constant incorporation of novel genotypes into the solutions that are already good - a mechanism we dub First Glances - and discovery of solutions through the exploration of neutral networks of different fitness levels - which we name Late Bloomers. On the other hand, Convection Selection uses fitness diversity techniques to give broken solutions time and shelter necessary to cross larger valleys in the fitness landscape - a mechanism we call Second Chances. In this work, we compare these two algorithms and their respective mechanisms over a range of numerical and 3D structure design optimization problems. We analyze the extent to which their mechanisms are utilized, and measure the impact of these mechanisms on finding good solutions.},
	doi = {10.1145/3638529.3654168},
	url = {http://www.framsticks.com/files/common/FitnessDiversityMechanismsInHFCAndConvectionSel.pdf},
	author = {Sofya Aksenyuk and Szymon Bujowski and Maciej Komosinski and Konrad Miazga}
}
@conference {2562,
	title = {Fitness Diversification in the Service of Fitness Optimization: a Comparison Study},
	booktitle = {Genetic and Evolutionary Computation Conference Companion (GECCO {\textquoteright}22)},
	year = {2022},
	publisher = {ACM},
	organization = {ACM},
	address = {Boston, USA},
	abstract = {Blindly chasing after fitness is not the best strategy for optimization of hard problems, as it usually leads to premature convergence and getting stuck in low-quality local optima. Several techniques such as niching or quality-diversity algorithms have been established that aim to alleviate the selective pressure present in evolutionary algorithms and to allow for greater exploration. Yet another group of methods which can be used for that purpose are fitness diversity methods. In this work we compare the standard single-population evolution against three fitness diversity methods: fitness uniform selection scheme (FUSS), fitness uniform deletion scheme (FUDS), and convection selection (ConvSel). We compare these methods on both mathematical and evolutionary design benchmarks over multiple parametrizations. We find that given the same computation time, fitness diversity methods regularly surpass the performance of the standard single-population evolutionary algorithm.},
	doi = {10.1145/3520304.3528949},
	url = {http://www.framsticks.com/files/common/FitnessDiversity.pdf},
	author = {Kamil Basiukajc and Maciej Komosinski and Konrad Miazga}
}
@article {2342,
	title = {Mappism: formalizing classical and artificial life views on mind and consciousness},
	journal = {Foundations of Computing and Decision Sciences},
	volume = {44},
	number = {1},
	year = {2019},
	pages = {55{\textendash}99},
	doi = {10.2478/fcds-2019-0005},
	url = {http://www.framsticks.com/files/common/MappismConsciousness.pdf},
	author = {Iwo B{\l}{\k a}dek and Maciej Komosinski and Konrad Miazga}
}
@inbook {2349,
	title = {Measuring properties of movement in populations of evolved 3D agents},
	booktitle = {Artificial Life Conference Proceedings},
	year = {2019},
	pages = {485{\textendash}492},
	publisher = {MIT Press},
	organization = {MIT Press},
	doi = {10.1162/isal_a_00208},
	author = {Maciej Komosinski and Konrad Miazga},
	editor = {Harold Fellermann and Jaume Bacardit and Angel Goni-Moreno and Rudolf M. F{\"u}chslin}
}
@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 Topa, Pawe{\l} and Jaros{\l}aw Tyszka},
	editor = {Gruca, Aleksandra and Brachman, Agnieszka and Kozielski, Stanis{\l}aw and Czach{\'o}rski, Tadeusz}
}
@inbook {2346,
	title = {eVolutus: a configurable platform designed for ecological and evolutionary experiments tested on Foraminifera},
	booktitle = {Man{\textendash}Machine Interactions 4},
	year = {2016},
	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}
}
@mastersthesis {Deback-2006thesis,
	title = {Eco-evolutionary experiments with situated agents},
	year = {2006},
	type = {masters},
	url = {http://www.framsticks.com/files/common/MSc_deBack_EcologyEvolution.pdf},
	author = {Walter de Back}
}
@article {Deback-2006,
	title = {Red Queen dynamics in a predator-prey ecosystem},
	journal = {Proceedings of the 8th annual conference on genetic and evolutionary computation},
	year = {2006},
	pages = {381{\textendash}382},
	publisher = {ACM New York, NY, USA},
	url = {http://www.ai.rug.nl/~mwiering/GROUP/ARTICLES/redqueen.pdf},
	author = {Walter de Back and M. Wiering and E. de Jong}
}
@book {Komosinski-and-Rotaru-Varga-2000,
	title = {From Directed to Open-Ended Evolution in a Complex Simulation Model},
	series = {Artificial Life VII},
	year = {2000},
	pages = {293{\textendash}299},
	publisher = {MIT Press},
	organization = {MIT Press},
	keywords = {Agents, AL, Simulation, Theory},
	author = {Maciej Komosinski and Adam Rotaru-Varga},
	editor = {Mark A. Bedau and John S. McCaskill and Norman H. Packard and Steen Rasmussen}
}
