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Komunikace a paměť pro plausibilní agenty
Kopal, Vojtěch ; Sýkora, Ondřej (advisor) ; Plch, Tomáš (referee)
In the present work we have focused on comparation of different implementation of memory for plausible agents in multi-agent environment. I have created a simulation whereby the agent are strangling to fulfill their need to eat. To succeed they have to learn the locations of food resources using the implemented spatial memory and an ability to communicate with each other. Later the agents are evaluated according to the level of hunger throughout the simulation.
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Modern regression methods in data mining
Kopal, Vojtěch ; Holeňa, Martin (advisor) ; Gemrot, Jakub (referee)
The thesis compares several non-linear regression methods on synthetic data sets gen- erated using standard benchmarks for a continuous black-box optimization. For that com- parison, we have chosen the following regression methods: radial basis function networks, Gaussian processes, support vector regression and random forests. We have also included polynomial regression which we use to explain the basic principles of regression. The com- parison of these methods is discussed in the context of black-box optimization problems where the selected methods can be applied as surrogate models. The methods are evalu- ated based on their mean-squared error and on the Kendall's rank correlation coefficient between the ordering of function values according to the model and according to the function used to generate the data. 1
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Modern regression methods in data mining
Kopal, Vojtěch ; Holeňa, Martin (advisor) ; Gemrot, Jakub (referee)
The thesis compares several non-linear regression methods on synthetic data sets gen- erated using standard benchmarks for a continuous black-box optimization. For that com- parison, we have chosen the following regression methods: radial basis function networks, Gaussian processes, support vector regression and random forests. We have also included polynomial regression which we use to explain the basic principles of regression. The com- parison of these methods is discussed in the context of black-box optimization problems where the selected methods can be applied as surrogate models. The methods are evalu- ated based on their mean-squared error and on the Kendall's rank correlation coefficient between the ordering of function values according to the model and according to the function used to generate the data. 1
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Komunikace a paměť pro plausibilní agenty
Kopal, Vojtěch ; Sýkora, Ondřej (advisor) ; Plch, Tomáš (referee)
In the present work we have focused on comparation of different implementation of memory for plausible agents in multi-agent environment. I have created a simulation whereby the agent are strangling to fulfill their need to eat. To succeed they have to learn the locations of food resources using the implemented spatial memory and an ability to communicate with each other. Later the agents are evaluated according to the level of hunger throughout the simulation.
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