An alternative formulation will now be given to help understand the
connection to I-spaces of a set of environments. The state space, as
defined previously, could instead be defined as a configuration
space,
. Let
denote a configuration.
Suppose that each possible environment corresponds to one way to
assign costs to all of the edges in a configuration transition graph.
The set
of all possible environments for this problem seems to
be all possible ways to assign costs,
. The state space can
now be defined as
, and for each state,
, the configuration and complete set of costs are specified.
Initially, it is guessed that the robot is in some particular
. If a cost mismatch is discovered, this means that a different
environment model is now assumed because a transition cost is
different from what was expected. The costs should actually be
written as
, which indicates the dependency of the
costs on the particular environment is assumed.
A nondeterministic I-state corresponds to a set of possible cost
assignments, along with their corresponding configurations. Since the
method requires assigning costs that have not yet been observed, it
takes a guess and assumes that one particular environment in the
nondeterministic I-state is the correct one. As cost mismatches are
discovered, it is realized that the previous guess lies outside of the
updated nondeterministic I-state. Therefore, the guess is changed to
incorporate the new cost information. As this process evolves, the
nondeterministic I-state continues to shrink. Note, however, that in
the end, the robot may solve the problem while being incorrect about
the precise . Some tiles are never visited, and their true
costs are therefore unknown. A default assumption about their costs
was made to solve the problem; however, the true
can only be
known if all tiles are visited. It is only true that the final
assumed default values lie within the final nondeterministic I-state.
Steven M LaValle 2020-08-14