- author = "Paul Grouchy and Gabriele M. T. D'Eleuterio",
- title = "Evolving Autonomous Agent Controllers as Analytical Mathematical Models",
- booktitle = "Proceedings of the Fourteenth International Conference of the Synthesis and Simulation of Living Systems, ALIFE 14",
- year = "2014",
- editor = "Hiroki Sayama and John Rieffel and Sebastian Risi and Rene Doursat and Hod Lipson",
- series = "Complex Adaptive Systems",
- pages = "681--688",
- address = "New York",
- month = "30 " # jul # "-2 " # aug,
- organisation = "International Society for Artificial Life",
- publisher = "MIT Press",
- keywords = "genetic algorithms, genetic programming, Evolvable Mathematical Models",
- isbn13 = "9780262326216 ?",
-
URL = "
https://www.mitpressjournals.org/doi/pdfplus/10.1162/978-0-262-32621-6-ch108",
-
DOI = "
doi:10.7551/978-0-262-32621-6-ch108",
- size = "8 pages",
- abstract = "A novel Artificial Life paradigm is proposed where autonomous agents are controlled via genetically encoded Evolvable Mathematical Models (EMMs). Agent/environment inputs are mapped to agent outputs via equation trees which are evolved using Genetic Programming. Equations use only the four basic mathematical operators: addition, subtraction, multiplication and division. Experiments on the discrete Double-T Maze with Homing problem are performed; the source code has been made available. Results demonstrate that autonomous controllers with learning capabilities can be evolved as analytical mathematical models of behaviour, and that neuroplasticity and neuromodulation can emerge within this paradigm without having these special functionalities specified a priori.",
-
notes = "University of Toronto Institute for Aerospace Studies,
Toronto, Ontario, Canada M3H 5T6
ALIFE 14 http://mitpress.mit.edu/books/artificial-life-14 ALIFE14NYC@gmail.com",
