Multi-agent actions under uncertainty: situation calculus, discrete time, plans and policies
IJCAI-97 Workshop on Nonmonotonic Reasoning, Action and Change Nagoya, Japan, Aug 1997.
We are working on a logic to combine the advantages of first-order
logic, but using Bayesian decision theory (or more generally game
theory) as a basis for handing uncertainty. This forms
a logic for multiple agents under uncertainty.
These agents act asynchronously, can have their own goals, have noisy
sensors, and imperfect effectors. Recently we have developed the
independent choice logic that incorporates all of these features. In
this paper we discuss two different representations of time within
this framework: the situation calculus and what is essentially the
event calculus. We show how they both can be used, and compare the
different ontological commitments made by each. Uncertainty is
handled in terms of a logic which allows for independent choices and
a logic program that gives the consequences of the choices. There are
probabilities over the choices by nature. As part of the consequences
are a specification of the utility of (final) states. In the situation
calculus, agents adopt programs and programs lead to situations in
possible worlds (which correspond to the possible outcomes of complete
histories); given a probability distribution over possible worlds, we
can get the expected utility of a program. In the event calculus view,
actions are propositions and agents adopt policies which are logic
programs to imply what the agent will do based on what it observes.
Again the expected value of a policy can be computed. The aim is to
choose the plan or policy that maximizes the expected utility. This
paper overviews both approaches, and explains why I think the event
calculus is the most promising approach.
You can get
You can also see the Slides
for the talk.
Last updated 23 April 97 - David Poole