Interplanetary Trajectory Planning with Monte Carlo Tree Search
Authors: Daniel Hennes, Dario Izzo
IJCAI 2015 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We discuss our experimental set-up, in particular parameter search and runtime analysis. We evaluate our approach on two well-known missions: Cassini-Huygens and Rosetta. |
| Researcher Affiliation | Academia | Daniel Hennes and Dario Izzo European Space Agency Advanced Concepts Team Noordwijk, The Netherlands daniel.hennes@esa.int, dario.izzo@esa.int |
| Pseudocode | No | The paper describes the MCTS steps in paragraph text and provides equations, but does not include formal pseudocode or an algorithm block. |
| Open Source Code | No | The paper does not provide any explicit statement or link for open-source code for the described methodology. |
| Open Datasets | Yes | For this computation we use the analytical planet ephemerides defined by NASA / Jet Propulsion Laboratory1. 1The approximated ephemerides were used as defined in http: //ssd.jpl.nasa.gov/?planet pos [accessed November 2014] |
| Dataset Splits | No | The paper describes a parameter search to tune the algorithm's parameters but does not specify training/test/validation dataset splits in the conventional sense for model evaluation. |
| Hardware Specification | No | The paper does not provide any specific details about the hardware used for running the experiments. |
| Software Dependencies | No | The paper does not list specific software dependencies with version numbers needed to replicate the experiment. |
| Experiment Setup | Yes | The UCB-1 (see Equation (1)) and ϵ-greedy (see Equation 2) selection policies require one parameter choice each. We sample 4000 parameter instances uniformly on a logarithmic scale. For each parameter instance, one run of UCT with the selected policy is performed until the computational budget of N Lambert legs is depleted. |