@article {114,
	title = {Properties of movement of 3D agents},
	number = {RA-1/2019},
	year = {2019},
	institution = {Poznan University of Technology, Institute of Computing Science},
	url = {http://www.framsticks.com/files/common/PropertiesOfMovementOf3DAgents.pdf},
	author = {Krzysztof Gorgolewski and Maciej Komosinski and Konrad Miazga and Krzysztof Rosinski and Pawe{\l} Rych{\l}y}
}
@inbook {108,
	title = {eVolutus: A New Platform for Evolutionary Experiments},
	booktitle = {Parallel Processing and Applied Mathematics: 11th International Conference, PPAM 2015, Krakow, Poland, September 6{\textendash}9, 2015. Revised Selected Papers, Part II},
	year = {2016},
	pages = {570{\textendash}580},
	publisher = {Springer},
	organization = {Springer},
	isbn = {978-3-319-32152-3},
	doi = {10.1007/978-3-319-32152-3_53},
	url = {http://dx.doi.org/10.1007/978-3-319-32152-3_53},
	author = {Topa, Pawe{\l} and Komosinski, Maciej and Tyszka, Jaros{\l}aw and Mensfelt, Agnieszka and Rokitta, Sebastian and Byrski, Aleksander and Bassara, Maciej},
	editor = {Wyrzykowski, Roman and Deelman, Ewa and Dongarra, Jack and Karczewski, Konrad and Kitowski, Jacek and Wiatr, Kazimierz}
}
@article {104,
	title = {Estimating similarity of neural network dynamics},
	number = {RA-10/10},
	year = {2010},
	institution = {Poznan University of Technology, Institute of Computing Science},
	abstract = {This report concerns estimation of the similarity between neural networks of any topology. Motivations and benefits of having an automated and quantitative network comparison mechanism are presented. The concept of neural network dynamics (neuron output signal) is considered. A measure is proposed for estimating similarity of active (i.e., working) neural networks. Properties of the measure are analyzed theoretically and verified empirically. The experiments have been performed on a set of evolved networks responsible for controlling 3D structures (agents, robots). These experiments demonstrate the capabilities and the limitations of the proposed measure as a mechanism to support humans in analyzing large sets of neural networks.},
	url = {http://www.framsticks.com/files/common/SimilarityNeuralNetworkDynamics.pdf},
	author = {Maciej Komosinski and Krzysztof Rosinski}
}
@article {Komosinski-and-Rotaru-Varga-2001,
	title = {Comparison of different genotype encodings for simulated 3D agents},
	journal = {Artificial Life Journal},
	volume = {7},
	number = {4},
	year = {2001},
	month = {Fall},
	pages = {395{\textendash}418},
	publisher = {MIT Press},
	address = {Cambridge, MA},
	abstract = {This paper analyzes the effect of different genetic encodings used for evolving 3D agents with physical morphologies. The complex phenotypes used in such systems often require nontrivial encodings. Different encodings used in Framsticks - a system for evolving 3D agents - are presented. These include a low-level direct mapping and two higher-level encodings: a recurrent and a developmental one. Quantitative results are presented from three simple optimization tasks (active height, passive height, and locomotion speed). The low-level encoding produced solutions of lower fitness than the two higher-level encodings under similar conditions. Results from recurrent and developmental encodings had similar fitness values but displayed qualitative differences. Desirable advantages and some drawbacks of more complex encodings are established.},
	keywords = {Agents, AL, Body and Brain evol., Genetics, Simulation, Theory},
	doi = {10.1162/106454601317297022},
	url = {http://www.framsticks.com/files/common/ComparisonGeneticEncodings3DAgents.pdf},
	author = {Maciej Komosinski and Adam Rotaru-Varga}
}
