AI/ML

Neuro-evolutionary Frameworks for Generalized Learning Agents. (arXiv:2002.01088v1 [cs.AI])




The recent successes of deep learning and deep reinforcement learning have
firmly established their statuses as state-of-the-art artificial learning
techniques. However, longstanding drawbacks of these approaches, such as their
poor sample efficiencies and limited generalization capabilities point to a
need for re-thinking the way such systems are designed and deployed. In this
paper, we emphasize how the use of these learning systems, in conjunction with
a specific variation of evolutionary algorithms could lead to the emergence of
unique characteristics such as the automated acquisition of a variety of
desirable behaviors and useful sets of behavior priors. This could pave the way
for learning to occur in a generalized and continual manner, with minimal
interactions with the environment. We discuss the anticipated improvements from
such neuro-evolutionary frameworks, along with the associated challenges, as
well as its potential for application to a number of research areas.

Source link







WordPress database error: [Error writing file '/tmp/MYFZ4FDD' (Errcode: 28 - No space left on device)]
SELECT SQL_CALC_FOUND_ROWS wp_posts.ID FROM wp_posts LEFT JOIN wp_term_relationships ON (wp_posts.ID = wp_term_relationships.object_id) WHERE 1=1 AND wp_posts.ID NOT IN (336888) AND ( wp_term_relationships.term_taxonomy_id IN (313) ) AND wp_posts.post_type = 'post' AND (wp_posts.post_status = 'publish') GROUP BY wp_posts.ID ORDER BY RAND() LIMIT 0, 3

This website uses cookies to improve your experience. We'll assume you're ok with this, but you can opt-out if you wish. Accept Read More

Privacy & Cookies Policy