Neuro-evolutionary Frameworks for Generalized Learning Agents

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.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
04/05/2019

Reducing catastrophic forgetting when evolving neural networks

A key stepping stone in the development of an artificial general intelli...
research
06/20/2023

Evolutionary Strategy Guided Reinforcement Learning via MultiBuffer Communication

Evolutionary Algorithms and Deep Reinforcement Learning have both succes...
research
06/01/2011

Evolutionary Algorithms for Reinforcement Learning

There are two distinct approaches to solving reinforcement learning prob...
research
10/26/2022

ERL-Re^2: Efficient Evolutionary Reinforcement Learning with Shared State Representation and Individual Policy Representation

Deep Reinforcement Learning (Deep RL) and Evolutionary Algorithm (EA) ar...
research
01/16/2019

Evolutionarily-Curated Curriculum Learning for Deep Reinforcement Learning Agents

In this paper we propose a new training loop for deep reinforcement lear...
research
04/13/2021

Podracer architectures for scalable Reinforcement Learning

Supporting state-of-the-art AI research requires balancing rapid prototy...
research
01/18/2023

A Domain-Agnostic Approach for Characterization of Lifelong Learning Systems

Despite the advancement of machine learning techniques in recent years, ...

Please sign up or login with your details

Forgot password? Click here to reset