Measuring fitness effects of agent-environment interactions
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Published version
Author(s)
McGregor, Simon
Mediano, Pedro AM
Type
Journal Article
Abstract
One important sense of the term “adaptation” is the process by which an agent changes appropriately in response to new information provided by environmental stimuli. We propose a novel quantitative measure of this phenomenon, which extends a little-known definition of adaptation as “increased robustness to repeated perturbation” proposed by Klyubin (2002). Our proposed definition essentially corresponds to the average value (relative to some fitness function) of state changes that are caused by the environment (in some statistical ensemble of environments). We compute this value by comparing the agent's actual fitness with its fitness in a counterfactual world where the causal links between agent and environment are disrupted. The proposed measure is illustrated in a simple Markov chain model and also using a recent model of autopoietic agency in a simulated protocell.
Date Issued
2018
Date Acceptance
2018-11-01
Citation
Artificial Life, 2018, 24 (3), pp.199-217
ISSN
1064-5462
Publisher
Massachusetts Institute of Technology Press
Start Page
199
End Page
217
Journal / Book Title
Artificial Life
Volume
24
Issue
3
Copyright Statement
© 2018 Massachusetts Institute of Technology. Simon McGregor, Pedro A. M. Mediano; Measuring Fitness Effects of Agent-Environment Interactions. Artif Life 2018; 24 (3): 199–217. doi: https://doi.org/10.1162/artl_a_00269 (https://direct.mit.edu/artl)
Identifier
https://direct.mit.edu/artl/article/24/3/199/2903/Measuring-Fitness-Effects-of-Agent-Environment
Subjects
Adaptivity
causal probability theory
Computer Science
Computer Science, Artificial Intelligence
Computer Science, Theory & Methods
information agent framework
Science & Technology
Technology
viability
Publication Status
Published
Date Publish Online
2018-11-01