From 8461f9c259303a14361e5f98df7c0889bb2e3fb4 Mon Sep 17 00:00:00 2001 From: David Eriksson Date: Fri, 20 Dec 2019 14:42:16 +0100 Subject: [PATCH] Update README.md --- README.md | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/README.md b/README.md index 0ef2d52..2e05e36 100644 --- a/README.md +++ b/README.md @@ -1,4 +1,4 @@ -## Overview +## Overview This is the code-release for the TuRBO algorithm from ***Scalable Global Optimization via Local Bayesian Optimization*** appearing in NeurIPS 2019. This is an implementation for the noise-free case and may not work well if observations are noisy as the center of the trust region should be chosen based on the posterior mean in this case. @@ -9,7 +9,7 @@ Note that TuRBO is a **minimization** algorithm, so please make sure you reformu ### Robot pushing The original code for the robot pushing problem is available at https://github.com/zi-w/Ensemble-Bayesian-Optimization. We have made the following changes to the code when running our experiments: -1. We turned off the visualization, which speeds up the function evaluations. +1. We turned off the visualization, which speeds up the function evaluations. 2. We replaced all instances of ```np.random.normal(0, 0.01)``` by ```np.random.normal(0, 1e-6)``` in ```push_utils.py```. This makes the function close to noise-free. Another option is to average over several evaluations using the original code 3. We flipped the sign of the objective function to turn this into a minimization problem. @@ -50,7 +50,7 @@ def heuristic_Controller(s, w): return a ``` -We use the constraints 0 <= w_i <= 2 for all parameters. +We use the constraints 0 <= w_i <= 2 for all parameters. We use ```INITIAL_RANDOM = 1500.0``` to make the problem more challenging. For more information about the logic behind this controller and how to integrate it with ```gym```, take a look at the original heuristic controller source code: https://github.com/openai/gym/blob/master/gym/envs/box2d/lunar_lander.py#L364 @@ -70,7 +70,7 @@ hubble: [52.5, 100] temp_cmb: [2.7, 2.8] hefrac: [0.2, 0.3] mneu: [2.9, 3.09] -scalar_amp: [1.5e-9, 2.6e-8] +scalar_amp: [1.5e-9, 2.6e-8] scalar_spec_ind: [0.72, 5] rf_fudge: [0, 100] rf_fudge_he: [0, 100]