Ortus: an Emotion-Driven Approach to (artificial) Biological Intelligence

TL;DR

Ortus is a biologically-inspired virtual organism designed to explore artificial intelligence through mechanisms like chemical synapses, gap junctions, and emotion-driven learning, aiming to model complex biological behaviors.

Contribution

Introduces Ortus, a virtual organism implementing biologically plausible neural mechanisms and emotion-driven learning to advance biologically-based artificial intelligence research.

Findings

Demonstrated a cyclic respiratory circuit in Ortus

Showcased emotionally-driven associative learning

Discussed future directions for biologically-inspired AI systems

Abstract

Ortus is a simple virtual organism that also serves as an initial framework for investigating and developing biologically-based artificial intelligence. Born from a goal to create complex virtual intelligence and an initial attempt to model C. elegans, Ortus implements a number of mechanisms observed in organic nervous systems, and attempts to fill in unknowns based upon plausible biological implementations and psychological observations. Implemented mechanisms include excitatory and inhibitory chemical synapses, bidirectional gap junctions, and Hebbian learning with its Stentian extension. We present an initial experiment that showcases Ortus' fundamental principles; specifically, a cyclic respiratory circuit, and emotionally-driven associative learning with respect to an input stimulus. Finally, we discuss the implications and future directions for Ortus and similar systems.