Real-Time GA-Based Probabilistic Programming in Application to Robot Control

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@InProceedings{Potapov:2016:AGI,

• author = "Alexey Potapov and Sergey Rodionov and Vita Potapova",
• title = "Real-Time GA-Based Probabilistic Programming in Application to Robot Control",
• booktitle = "Artificial General Intelligence",
• year = "2016",
• editor = "Bas Steunebrink and Pei Wang and Ben Goertzel",
• volume = "9782",
• series = "LNCS",
• pages = "95--105",
• publisher = "Springer",
• keywords = "genetic algorithms, genetic programming",
• isbn13 = "978-3-319-41649-6",
• DOI = "doi:10.1007/978-3-319-41649-6_10",
• abstract = "Possibility to solve the problem of planning and plan recovery for robots using probabilistic programming with optimization queries, which is being developed as a framework for AGI and cognitive architectures, is considered. Planning can be done directly by introducing a generative model for plans and optimizing an objective function calculated via plan simulation. Plan recovery is achieved almost without modifying optimization queries. These queries are simply executed in parallel with plan execution by a robot meaning that they continuously optimize dynamically varying objective functions tracking their optima. Experiments with the NAO robot showed that replanning can be naturally done within this approach without developing special plan recovery methods.",

}

Genetic Programming entries for Alexey Potapov Sergey Rodionov Vita Potapova

Citations