Authors:
Anshul Joshi
;
Thomas C. Henderson
and
Wenyi Wang
Affiliation:
University of Utah, United States
Keyword(s):
Concept Representation, Wreath Product, Perceptual Organization, Bayesian Network.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Artificial Intelligence and Decision Support Systems
;
Bayesian Networks
;
Cognitive Systems
;
Computational Intelligence
;
Enterprise Information Systems
;
Evolutionary Computing
;
Knowledge Representation and Reasoning
;
Soft Computing
;
Symbolic Systems
Abstract:
(Leyton, 2001) proposes a generative theory of shape, and general cognition, based on group actions on sets
as defined by wreath products. This representation relates object symmetries to motor actions which produce
those symmetries. Our position expressed here is that this approach provides a strong basis for robot cognition
when:
1. sensory data and motor data are tightly coupled during analysis,
2. specific instances and general concepts are structured this way, and
3. uncertainty is characterized using a Bayesian framework.
Our major contributions are (1) algorithms for symmetry detection and to realize wreath product analysis, and
(2) a Bayesian characterization of the uncertainty in wreath product concept formation.