ASIMOV* is an agent-based simulation of decision-making processes in foraging. It provides a fundamental framework for developing artificial animal behavior and cognition through stepwise modifications, where pre-existing circuitry is plausibly modified for changing function and tested, as happens in natural evolution. ASIMOV was built on an earlier simulation, Cyberslug, itself based on the behaviors and neuronal circuitry of the simple predatory sea slug Pleurobranchaea californica. In Cyberslug, a forager affectively integrates sensation, motivation (hunger), and learning to make cost-benefit decisions for approach or avoidance of prey. ASIMOV builds on this with the explicit implementation of reward experience, pain, and homeostatic plasticity to provide realistic valuation of stimuli, and demonstrates how the nature and course of the addiction process emerges as an extreme expression of aesthetic preference.
ASIMOV is being further developed with the addition of the Feature Association Matrix (FAM) to enable the formation of simple episodic memory. This allows the ASIMOV agent to create spatial maps of its environment to use to maximize the rewards that it obtains in foraging. The FAM is an abstraction of physiological circuits implicated in episodic memory, such as the auto- and hetero-associative circuits of the hippocampus.
*ASIMOV – short for “Algorithm of Selectivity by Incentive and Motivation for Optimized Valuation"
For more details please see our website and publication:
Gribkova, E. D., Catanho, M., & Gillette, R. (2020). Simple Aesthetic Sense and Addiction Emerge in Neural Relations of Cost-Benefit Decision in Foraging. Scientific reports, 10(1), 1-11. https://doi.org/10.1038/s41598-020-66465-0
To run ASIMOV and inspect the code, the multi-agent modeling program NetLogo must be acquired from https://ccl.northwestern.edu/netlogo/.