An Integrative Methodology for Teaching Embodied Non-Linguistic Agents, Applied to Virtual Animals in Second Life

A teaching methodology called Imitative-Reinforcement-Corrective (IRC) learning is described, and proposed as a general approach for teaching embodied non-linguistic AGI systems. IRC may be used with a variety of different learning algorithms, but it is particularly easily described in EC lingo. In these terms, it is a framework for automatically learning a procedure that generates a desired type of behavior, in which: a set of exemplars of the target behavior-type are utilized for fitness estimation; reinforcement signals from a human teacher are used for fitness evaluation; and the execution of candidate procedures may be modified by the teacher via corrections delivered in real-time. An example application of IRC to teach behaviors to AI-controlled artificial animals embodied in the Second Life virtual world is described in detail, including a review of the overall virtual-animal-control software architecture and how the integrative teaching/learning methodology fits into it. In thi...

• Type: Conference
• Year: 2008
• Where: AGI
• Authors: Ben Goertzel, Cassio Pennachin, Nil Geisweiller, Moshe Looks, Andre Senna, Welter Silva, Ari Heljakka, Carlos Lopes
• Keywords: AGI 2008, Artificial Intelligence, Embodied Non-linguistic Agi, Example Application, Learning Algorithm