December 2021

Behavioural Plasticity Can Help Evolving Agents in Dynamic Environments But at the Cost of Volatility

Chloe M. Barnes, Anikó Ekárt, Kai Olav Ellefsen, Kyrre Glette, Peter R. Lewis, Jim Tørresen: Behavioural Plasticity Can Help Evolving Agents in Dynamic Environments But at the Cost of Volatility. In: ACM Transactions on Autonomous Adaptive Systems, vol. 15, no. 4, 2021.

Abstract

Neural networks have been widely used in agent learning architectures; however, learnings for one task might nullify learnings for another. Behavioural plasticity enables humans and animals alike to respond to environmental changes without degrading learned knowledge; this can be achieved by regulating behaviour with neuromodulation—a biological process found in the brain. We demonstrate that by modulating activity-propagating signals, neurally trained agents evolving to solve tasks in dynamic environments that are prone to change can expect a significantly higher fitness than non-modulatory agents and also achieve their goals more often. Further, we show that while behavioural plasticity can help agents to achieve goals in these variable environments, this ability to overcome environmental changes with greater success comes at the cost of highly volatile evolution.


BibTeX (Download)

@article{Barnes2021BehaviouralVolatility,
title = {Behavioural Plasticity Can Help Evolving Agents in Dynamic Environments But at the Cost of Volatility},
author = {Chloe M. Barnes and Anikó Ekárt and Kai Olav Ellefsen and Kyrre Glette and Peter R. Lewis and Jim Tørresen},
doi = {10.1145/3487918},
year  = {2021},
date = {2021-12-20},
urldate = {2021-01-01},
journal = {ACM Transactions on Autonomous Adaptive Systems},
volume = {15},
number = {4},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
abstract = {Neural networks have been widely used in agent learning architectures; however, learnings for one task might nullify learnings for another. Behavioural plasticity enables humans and animals alike to respond to environmental changes without degrading learned knowledge; this can be achieved by regulating behaviour with neuromodulation—a biological process found in the brain. We demonstrate that by modulating activity-propagating signals, neurally trained agents evolving to solve tasks in dynamic environments that are prone to change can expect a significantly higher fitness than non-modulatory agents and also achieve their goals more often. Further, we show that while behavioural plasticity can help agents to achieve goals in these variable environments, this ability to overcome environmental changes with greater success comes at the cost of highly volatile evolution.},
keywords = {Agent-Based Systems, ANNs, Artificial Life, Behavioural Plasticity, Evolutionary Algorithms, Evolutionary Volatility, Neuroevolution, Neuromodulation, River Crossing},
pubstate = {published},
tppubtype = {article}
}