| Manu | Date: Tuesday, 02-March-2021, 6:02 PM | Message # 1 |
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| Scientists have come up with a computer program that can master a variety of 1980s exploration games, paving the way for more self-sufficient robots.
They created a family of algorithms (software-based instructions for solving a problem) able to complete classic Atari games, such as Pitfall.
Previously, these scrolling platform games have been challenging to solve using artificial intelligence (AI).
The algorithms could help robots better navigate real-world environments.
This remains a core challenge in the fields of robotics and artificial intelligence. The types of environments in question include disaster zones, where robots could be sent out to search for survivors, or even just the average home.
The work in this study falls into an area of AI research known as reinforcement learning.
A number of games used in the research require the user to explore mazes containing rewards, obstacles and hazards. The family of algorithms, known collectively as Go-Explore, produced substantial improvements on previous attempts to solve games such as the wittily titled Montezuma's Revenge, released in 1984, Freeway (1981) and the aforementioned Pitfall (1982).
One way the researchers did this was by developing algorithms that build up archives of areas they have already visited.
Read more/ full article source - https://www.bbc.com/news/science-environment-56194855
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