Geography, geology, ecology - Sections of geology. Crosswordist's Handbook

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CROSSWORD HANDBOOK
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Reference book crossword. Quick word search by mask. Branches of geology

Crosswordist's Handbook / Index

Crosswordist's Handbook

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Geography, geology, ecology / Geology / Branches of geology

(8)

GEODESY - about measurements on the surface of the Earth for displaying it on maps

GEOCHEMISTRY

(9)

GEOPHYSICS

CRYOLOGY

LITHOLOGY - about sedimentary rocks

ORGRAPHY - about the relief of the earth's crust

TECTONICS (geotectonics) - about the development of the structure of the earth's crust

(10)

HYDROLOGY - the science of natural waters

PETROLOGY (petrography) - about rocks

PETROCHEMISTRY - about the distribution of chemical elements in rocks

(11)

GEOACOUSTICS - about the propagation of vibrations in the earth's crust

HYDROGRAPHY - 1) a section of hydrology, about fresh water, 2) the science of shipping lanes

GLACIOLOGY - about glaciers

MINERALOGY - about minerals and their properties

PETROGRAPHY - see Petrology

PETROPHYSICS - about the relationship between the physical properties of rocks and their composition

SEISMOLOGY - about fluctuations of the earth's crust

SPELEOLOGY - about caves

(12)

VOLCANOLOGY

GEOCRYOLOGY - see Permafrost

GEOTECTONICS - see Tectonics

SEISMOGRAPHY - about methods of fixing and studying the vibrations of the earth's crust

STRATIGRAPHY (geochronology) - a branch of geology, about the sequence of formation of rocks

(13)

GEOMORPHOLOGY - about the relief of the earth's crust

GEOCHRONOLOGY - see Stratigraphy

HYDROGEOLOGY - about groundwater

HYDROGEOCHEMISTRY - a section of hydrogeology, about the chemical composition of the hydrosphere

TECTONOPHYSICS - about the physical conditions for the occurrence of tectonic deformations

(14)

PALEOGEOGRAPHY - about fossil landscapes

(15)

CRYSTALLOGRAPHY

PERMAFROST (geocryology)

SEISMOTECTONICS - a branch of seismology, about the occurrence of earthquakes

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Robots have been taught to be curious 08.06.2017

For several years, developers of computer programs for robots have tried to create a "curiosity algorithm", but it was quite difficult to replicate human curiosity. According to them, most methods cannot assess the "gaps" in the knowledge of the robot and understand what it will be interested in.

However, Todd Hester of Google DeepMind in the UK and Peter Stone of the University of Texas in the US have managed to create an algorithm that allows a computer program to "be curious" by learning about its environment on its own. The new approach will allow robots to learn even faster than they do now. The researchers named the algorithm TEXPLORE-VENIR, which is based on a "reinforcement learning" technique.

This technique works according to the following principle: when the program approaches a solution to a problem (for example, exiting a maze), it receives some reward. It is assumed that, having received an award, in the future she will again try to achieve some goal. The researchers slightly modified the "reinforcement learning" technique so that the program is rewarded simply for new knowledge, even if it does not help achieve the goal. For example, TEXPLORE-VENIR earns bonuses when he explores the world, looks for distant places on the map, or masters cooking recipes.

Hester and Stone tested their algorithm in two scenarios. The first of these was a virtual maze of 4 rooms connected by locked doors. The bot - just a computer program - had to explore the area, find the key, take it and open the door. For each open door, he earned 10 points. To achieve the highest score, he was given 3000 "steps".

When using the TEXPLORE-VENIR algorithm, the bot explored the area (having spent 1000 "steps" on this), it earned 55 points. Moreover, if he used other algorithms, he received from 0 to 35 points. When the program had to explore the area and unlock the doors at the same time, it scored 70 points with TEXPLORE-VENIR, and less than 5 in other cases.

For the second experiment, the researchers connected the humanoid robot Nao. With the help of the TEXPLORE-VENIR algorithm, he had to complete three tasks: hit a musical cymbal, find and bring a pink ribbon to his eyes, and press a button located on his leg. For each task, Nao received 200 "steps", and another 400 "steps" were given to him for "training" (learning subjects). After 13 attempts, he pressed the button 7 times, hit the cymbal 1 out of 5 times, and eventually found the pink ribbon faster.

The TEXPLORE-VENIR algorithm showed good results, however, excessive curiosity can reduce the productivity of the robot, third-party researchers say. It may happen that the robot's intrinsic motivation to receive a learning reward exceeds its extrinsic motivation to complete the task. Therefore, it is important to find a balance between the two types of motivation.

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