S
smcder
Guest
Abstract
We present a formal framework that generalizes and subsumes the standard
Bayesian framework for vision. While incorporating the fundamental role of
probabilistic inference, our Computational Evolutionary Perception (CEP) framework
also incorporates fitness in a fundamental way, and it allows us to consider
different possible relationships between the objective world and perceptual representations
(e.g., in evolving visual systems).
In our framework, shape is not assumed
to be a reconstruction of an objective world property. It is simply a representational
format that has been tuned by natural selection to guide adaptive behavior. In brief,
shape is an effective code for fitness. Because fitness depends crucially on the actions
of an organism, shape representations are closely tied to actions. We model
this connection formally using the Perception-Decision-Action (PDA) loop. Among
other things, the PDA loop clarifies how, even though one cannot know the effects
of ones actions in the objective world itself, one can nevertheless know the results
of those effects back in our perceptions. This, in turn, explains how organisms can
interact effectively with a fundamentally unknown objective world.
We present a formal framework that generalizes and subsumes the standard
Bayesian framework for vision. While incorporating the fundamental role of
probabilistic inference, our Computational Evolutionary Perception (CEP) framework
also incorporates fitness in a fundamental way, and it allows us to consider
different possible relationships between the objective world and perceptual representations
(e.g., in evolving visual systems).
In our framework, shape is not assumed
to be a reconstruction of an objective world property. It is simply a representational
format that has been tuned by natural selection to guide adaptive behavior. In brief,
shape is an effective code for fitness. Because fitness depends crucially on the actions
of an organism, shape representations are closely tied to actions. We model
this connection formally using the Perception-Decision-Action (PDA) loop. Among
other things, the PDA loop clarifies how, even though one cannot know the effects
of ones actions in the objective world itself, one can nevertheless know the results
of those effects back in our perceptions. This, in turn, explains how organisms can
interact effectively with a fundamentally unknown objective world.