Indirect and Conditional Sensing in the Event Calculus
Jeremy Forth and Murray Shanahan
Abstract
Controlling the sensing of an environment by an agent has been accepted as
necessary for effective operation within most practical domains. Usually,
however, agents operate in partially observable domains where not all parameters
of interest are accessible to direct sensing. In such circumstances, sensing
actions must be chosen for what they will reveal indirectly, through an axiomatized
model of the domain causal structure, including ramifications. This article
shows how sensing can be chosen so as to acquire and use indirectly obtained
information to meet goals not otherwise possible. Classical logic Event Calculus
is extended with both a knowledge formalism and causal ramifications, and
is used to show how inferring unknown information about a domain leads to
conditional sensing actions.