Conference proceeding
Ortus: an Emotion-Driven Approach to (artificial) Biological Intelligence
FOURTEENTH EUROPEAN CONFERENCE ON ARTIFICIAL LIFE (ECAL 2017), pp.537-544
01 Jan 2017
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Ortus is a simple virtual organism that also serves as an initial framework for investigating and developing biologicallybased 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.
Metrics
2 Record Views
Details
- Title
- Ortus: an Emotion-Driven Approach to (artificial) Biological Intelligence
- Creators
- Andrew W. E. McDonald - Drexel Univ, Dept Comp Sci, Philadelphia, PA 19104 USASean Grimes - Drexel UniversityDavid E. Breen - Drexel University
- Contributors
- C Knibbe (Editor)G Beslon (Editor)D Parsons (Editor)D Misevic (Editor)J RouzaudCornabas (Editor)N Bredeche (Editor)S Hassas (Editor)O Simonin (Editor)H Soula (Editor)
- Publication Details
- FOURTEENTH EUROPEAN CONFERENCE ON ARTIFICIAL LIFE (ECAL 2017), pp.537-544
- Conference
- FOURTEENTH EUROPEAN CONFERENCE ON ARTIFICIAL LIFE (ECAL 2017), 14th
- Publisher
- Mit Press
- Number of pages
- 8
- Grant note
- NSF Graduate Research Fellowship Program; National Science Foundation (NSF)
- Resource Type
- Conference proceeding
- Language
- English
- Academic Unit
- Computer Science (Computing)
- Identifiers
- 991019170323504721
UN Sustainable Development Goals (SDGs)
This output has contributed to the advancement of the following goals:
InCites Highlights
These are selected metrics from InCites Benchmarking & Analytics tool, related to this output
- Web of Science research areas
- Computer Science, Interdisciplinary Applications
- Mathematical & Computational Biology