Action Perception
Robert Thibadeau
Seagate Research
The human perception of actions has barely been studied, but this
study of action perception promises to provide a wealth of interesting
hypotheses regarding cognitive processing. Action perception is
distinct from motion perception in that the direct perception of
causation is central to the percept. Among the interesting hypotheses
is that it can be hypothesized that what we know as thought and
reasoning is where we perceive and plan actions. Another hypothesis
is that what we know as logic and mathematics derives from our direct
perceptions of causation in the actions we perceive and think about.
I will present a study that attempts to estimate the scale of
computation needed to implement a system for visually perceiving
meaningful actions and non-trivially producing an English narration of
what is being visually perceived, as well as answering questions about
what is visually perceived. The scale of the computation for learning
could easily reach exaflops over distributed datasets (HADOOP or
MapReduce style).
This study is partly based on my work (Thibadeau, 1986), and Doug
Rohde's 2002 dissertation (http://tedlab.mit.edu:16080/~dr/Thesis/),
as well as Simon and Rescher (1966 see summary below). The study
includes an explicit proposal for extending Rohde's work to
multimodal, multisensory, processing.
(Simon and Rescher 1966 From Wikipedia, Causality)
Derivation theories
The Nobel Prize holder Herbert Simon and Philosopher Nicholas
Rescher[20] claim that the asymmetry of the causal relation is
unrelated to the asymmetry of any mode of implication that
contraposes. Rather, a causal relation is not a relation between
values of variables, but a function of one variable (the cause) on to
another (the effect). So, given a system of equations, and a set of
variables appearing in these equations, we can introduce an asymmetric
relation among individual equations and variables that corresponds
perfectly to our commonsense notion of a causal ordering. The system
of equations must have certain properties, most importantly, if some
values are chosen arbitrarily, the remaining values will be determined
uniquely through a path of serial discovery that is perfectly
causal. They postulate the inherent serialization of such a system of
equations may correctly capture causation in all empirical fields,
including physics and economics.