The Xzistor LAB is building a new agent (robot/simulation combo) that we refer to as our ‘Language Learning Infant Agent’.
Our new paper provides a theoretical basis for how artificial agents can develop a language learning capability using artificial emotions as defined by the Xzistor Mathematical Model of Mind. A multi-stage project is proposed to demonstrate how an Xzistor agent will develop a language skill like and infant and then refine this skill towards improved syntax and grammar use with further reinforcement learning. The paper provides two appendices covering the mathematical principles of the Xzistor brain model and an explanation of how it could potentially unify behaviorist and structuralist language theories.
Find new paper (preprint) here:
Artificial Agent Language Development based on the Xzistor Mathematical Model of Mind
The paper comes in 3 parts:
Part 1
Main Paper — Artificial Agent Language Development based on the Xzistor Mathematical Model of Mind
Part 2
Appendix A — Mathematical Principles of the Xzistor Brain Model
Part 3
Appendix B — Xzistor Brain Model Unification of Behaviorist and Structuralist Language Theories
QUOTES FROM THE PAPER
“If we want a different AI future, we need to start considering alternative approaches to contemporary generative AI…”
“A multi-stage project is proposed to demonstrate how an artificial Xzistor agent could systematically develop basic language skills…”
“The model’s mathematical framework offers insight into the underpinning logic of the biological brain…could reignite the quest for human-inspired AI.”
“Building an artificial agent with the skills of an infant that can learn to use language to communicate with humans…will be much more than just a demonstrator of the principles of verbal behavior — it could be the start of a new era of Artificial Intelligence (AI).”
“The Xzistor Mathematical Model of Mind provides many of the missing pieces of the puzzle — and comes with a proven safeguard against ‘runaway-intelligence’ rooted in physics.”
Reach out to us if you want to know more!
Xzistor LAB Team
