Logic-based AI is often thought of as being restricted to highly abstract domains such as theorem-proving and linguistic semantics. In the Novamente AGI architecture, however, probabilistic logic is used for a wider variety of purposes, including simple reinforcement learning of infantile behaviors, which are primarily concerned with perception and action rather than abstract cognition. This paper reports some simple experiments designed to validate the viability of this approach, via using the PLN probabilistic logic framework, implemented within the Novamente AGI architecture, to carry out reinforcement learning of simple embodied behaviors in a 3D simulation world (AGISim). The specific experiment focused upon involves teaching Novamente to play the game of “fetch” using reinforcement learning based on repeated partial rewards. Novamente is an integrative AGI architecture involving considerably more than just PLN; however, in this “fetch” experiment, the only cognitive process PLN is coupled with is simple perceptual pattern mining; other Novamente cognitive processes such as evolutionary learning and economic attention allocation are not utilized, so as to allow the study and demonstration of the power of PLN on its own.
IOS Press, Inc.
6751 Tepper Drive
Clifton, VA 20124
Tel.: +1 703 830 6300
Fax: +1 703 830 2300 email@example.com
(Corporate matters and books only) IOS Press c/o Accucoms US, Inc.
For North America Sales and Customer Service
West Point Commons
Lansdale PA 19446
Tel.: +1 866 855 8967
Fax: +1 215 660 5042 firstname.lastname@example.org