@article {Komosinski-and-Kups-2017r,
	title = {Evolutionary construction of derivations in classical propositional logic using a symbolic-connectionist representation},
	number = {RA{\textendash}3/17},
	year = {2017},
	institution = {Poznan University of Technology, Institute of Computing Science},
	type = {Research report},
	abstract = {This report introduces a way derivations in classical propositional logic can be constructed using evolutionary algorithms. The derivations are represented by connectionist systems. There are three kinds of nodes constituting these systems: formula nodes that generate signal in the form of strings of symbols, "modus ponens" nodes that transform incoming signal according to the "modus ponens" rule, and substitution nodes that transform incoming signal by applying the substitution rule. This work presents initial research on an approach that is a part of our quest for efficient construction of derivations using various logics and constrained in various ways. The final part of this report outlines limitations encountered in our initial experiments and the ways the proposed approach can be improved.},
	url = {http://www.framsticks.com/files/common/EvolutionOfDerivationsInLogic.pdf},
	author = {Maciej Komosinski and Adam Kups}
}
@article {Komosinski-and-Mensfelt-2016,
	title = {Emotions perceived and emotions experienced in response to computer-generated music},
	journal = {Music Perception},
	volume = {33},
	number = {4},
	year = {2016},
	month = {April},
	pages = {432{\textendash}445},
	publisher = {UC Press},
	abstract = {This paper explores perceived and experienced emotions elicited by computer-generated music. During the experiments, 30 participants listened to 20 excerpts. Each of the excerpts lasted for about 16 seconds and was generated in real-time by specifically designed software. Measurements were performed using both categorical (a free verbal description) and dimensional approaches. The relationship between structural factors of music (mode, tempo, pitch height, rhythm, articulation and presence of the dissonance) and emotions was examined. Personal characteristics of the listener: gender and musical training were also taken into account. The relationship between structural factors and the perceived emotions was mostly congruent with predictions derived from the literature, and the relationship between those factors and experienced emotions was very similar. Tempo and pitch height {\textendash} the cues common to music and speech {\textendash} turned out to have a strong influence on the evaluation of emotion. Personal factors had a marginal effect. In the case of verbal categories comparable with the dimensional model, a strong correspondence was found.},
	doi = {10.1525/MP.2016.33.4.432},
	url = {https://www.cs.put.poznan.pl/mkomosinski/research/music-emotions-perceived-and-experienced.pdf},
	author = {Maciej Komosinski and Agnieszka Mensfelt}
}
@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}
}
@article {116,
	title = {Evolutionary design of tall structures},
	year = {2012},
	institution = {Poznan University of Technology, Institute of Computing Science},
	issn = {RA-06/12},
	url = {http://www.framsticks.com/files/common/EvolutionaryDesignOfTallStructures.pdf},
	author = {Maciej Komosinski}
}
@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}
}
@conference {Komosinski-and-Polak-2009,
	title = {Evolving free-form stick ski jumpers and their neural control systems},
	booktitle = {Proceedings of the National Conference on Evolutionary Computation and Global Optimization},
	year = {2009},
	pages = {103--110},
	address = {Poland},
	abstract = {This paper concerns evolution of stick agents in a simplified ski-jumping task. Both body morphologies and control systems are optimized. Evolutionary processes are performed in a range of conditions: the air drag and the friction of the ramp varies. Qualitative and quantitative analyses are presented that show how jump distance, jump height, and flight trajectory depend on environmental conditions. Jumping and landing strategies are investigated, and the most interesting evolved behaviors are reported.},
	url = {http://www.framsticks.com/files/common/Komosinski_Polak_EvolvedSkiJumping.pdf},
	author = {Maciej Komosinski and Jan Polak}
}
@article {Hapke-and-Komosinski-2008,
	title = {Evolutionary Design of Interpretable Fuzzy Controllers},
	journal = {Foundations of Computing and Decision Sciences},
	volume = {33},
	number = {4},
	year = {2008},
	pages = {351{\textendash}367},
	abstract = {This paper presents an approach that allows to evolve fuzzy controllers that can be expressed as fuzzy rules in human-readable form and interpreted. For comparison, the evolution is also performed on simple neural controllers. The control task considered here is a balancing problem, where a construct made of articulated elastic elements is equipped with sensors and actuators. The goal of the construct is to keep the top heavy part from touching the ground. Evolved controllers are evaluated using computer simulation. Control systems process signals from tilt sensors to actuators fixed in the construct. During evolution, fuzzy controllers (including their fuzzy sets and rules) are reconfigured by genetic operators in order to maximize fitness of the control. The article compares evolvability of neural and fuzzy controllers and demonstrates how additional, comprehensible knowledge can be gained which explains the work of the fuzzy controller. The representation for the fuzzy control system, evolutionary operators, various evaluation functions, and the best evolved control systems are presented. A sample evolved fuzzy control system is analyzed in detail to explain its behavior.},
	url = {http://www.framsticks.com/files/common/Komosinski_EvolveInterpretableFuzzy.pdf},
	author = {Maciej Hapke and Maciej Komosinski}
}
@booklet {Hapke-et-al-2002,
	title = {Evolutionary optimization of fuzzy controllers for virtual robots},
	number = {RA-010/02},
	year = {2002},
	publisher = {Poznan University of Technology, Institute of Computing Science},
	keywords = {EA, Fuzzy, Robotics},
	author = {Maciej Hapke and Maciej Komosinski and Dawid Waclawski}
}
@article {Komosinski-et-al-2001,
	title = {On estimating similarity of artificial and real organisms},
	journal = {Theory in Biosciences},
	volume = {120},
	number = {3-4},
	year = {2001},
	month = {December},
	pages = {271{\textendash}286},
	keywords = {AL, Biology, EA, Theory},
	url = {http://www.framsticks.com/files/common/Komosinski_Similarity_TheoryInBiosc2001.pdf},
	author = {Maciej Komosinski and Grzegorz Koczyk and Marek Kubiak}
}
@booklet {Komosinski-et-al-2001r,
	title = {Ewolucyjna optymalizacja fraz muzycznych sterowana przez cz{\l}owieka},
	number = {RB-008/01},
	year = {2001},
	publisher = {Poznan University of Technology, Institute of Computing Science},
	keywords = {AL, EA, Philosophy, Psychology},
	author = {Maciej Komosinski and Jerzy Blaszczynski and Marcin Szymanski}
}
@article {Komosinski-and-Krawiec-2000,
	title = {Evolutionary weighting of image features for diagnosing of CNS tumors},
	journal = {Artificial Intelligence In Medicine, Special Issue on Evolutionary Computation in Medicine},
	volume = {19},
	number = {1},
	year = {2000},
	pages = {25{\textendash}38},
	keywords = {CI, EA},
	doi = {10.1016/S0933-3657(99)00048-2},
	url = {https://www.cs.put.poznan.pl/mkomosinski/research/evolutionary-weighting-image-features-for-diagnosing-CNS-tumors.pdf},
	author = {Maciej Komosinski and Krzysztof Krawiec}
}
@booklet {Komosinski-and-Lapacz-1999,
	title = {Evolutionary weighting of features for classification},
	number = {RA-007/99},
	year = {1999},
	publisher = {Poznan University of Technology, Institute of Computing Science},
	keywords = {CI, EA},
	author = {Maciej Komosinski and Roman}
}
