This thesis aims to explore how different factors can affect the search performance of evolutionary algorithms. Additionally how applying different mutation techniques changes the overall search performance of rtNEAT. This thesis demonstrates how mutation affects exploration and exploitation when optimizing for a 3-input XOR gate as well as optimizing agent movements in a real time environment. This thesis is also provided as a guideline in the development of an evolutionary algorithm, particularly the implementation of rtNEAT algorithm, and a simple game environment in Python.Masteroppgave i informasjonsvitenskapINFO390MASV-INF
International audienceWhen looking for relevant mutations of a learning program, a main trouble is t...
Machine learning is an important part of most current Artificial Intelligence applications as it all...
Recent development of large databases, especially those in genetics and proteomics, is pushing the d...
This thesis aims to explore how different factors can affect the search performance of evolutionary ...
Evolutionary computation has been around ever since the late 50s. This thesis aims at elaborate on g...
This paper describes the EvoTanks research project, a continuing attempt to develop strong AI player...
This paper describes the EvoTanks research project, a continuing attempt to develop strong AI player...
This paper reports on experiments investigating the use of Evolutionary Algorithms to train Artifici...
Exploiting knowledge to guide the evolutionary process in evolutionary computing is a concept that h...
One of the core functions in most Evolutionary Algorithms is mutation. In complex search spaces, whi...
International audienceWhen looking for relevant mutations of a learning program, a main trouble is t...
A significant challenge in genetic programming is premature convergence to local optima, which often...
A significant challenge in genetic programming is premature convergence to local optima, which often...
International audienceWhen looking for relevant mutations of a learning program, a main trouble is t...
International audienceWhen looking for relevant mutations of a learning program, a main trouble is t...
International audienceWhen looking for relevant mutations of a learning program, a main trouble is t...
Machine learning is an important part of most current Artificial Intelligence applications as it all...
Recent development of large databases, especially those in genetics and proteomics, is pushing the d...
This thesis aims to explore how different factors can affect the search performance of evolutionary ...
Evolutionary computation has been around ever since the late 50s. This thesis aims at elaborate on g...
This paper describes the EvoTanks research project, a continuing attempt to develop strong AI player...
This paper describes the EvoTanks research project, a continuing attempt to develop strong AI player...
This paper reports on experiments investigating the use of Evolutionary Algorithms to train Artifici...
Exploiting knowledge to guide the evolutionary process in evolutionary computing is a concept that h...
One of the core functions in most Evolutionary Algorithms is mutation. In complex search spaces, whi...
International audienceWhen looking for relevant mutations of a learning program, a main trouble is t...
A significant challenge in genetic programming is premature convergence to local optima, which often...
A significant challenge in genetic programming is premature convergence to local optima, which often...
International audienceWhen looking for relevant mutations of a learning program, a main trouble is t...
International audienceWhen looking for relevant mutations of a learning program, a main trouble is t...
International audienceWhen looking for relevant mutations of a learning program, a main trouble is t...
Machine learning is an important part of most current Artificial Intelligence applications as it all...
Recent development of large databases, especially those in genetics and proteomics, is pushing the d...