@conference {1510243,
	title = {Integrating Belief-Desire-Intention Approaches with POMDPs: The Case of Team-Oriented Programs },
	booktitle = {AAAI Spring Symposium on Logical Formalisms for Commonsense Reasoning},
	year = {2003},
	abstract = {
Integrating approaches based on belief-desire-intentions
(BDI) logics with the more recent developments of distributed POMDPs is today a fundamental challenge in the
multiagent systems arena. One common suggestion for such
an integration is to use stochastic models (POMDPs) for generating agent behaviors, while using the BDI components for
monitoring and creating explanations. We propose a completely inverse approach, where the BDI components are used
to generate agent behaviors, and distributed POMDPs are
used in an analysis mode. In particular, we focus on teamoriented programs for tasking multiagent teams, where the
team-oriented programs specify hierarchies of team plans that
the team and its subteams must adopt as their joint intentions.
However, given a limited number of agents, finding a good
way to allocate them to different teams and subteams to execute such a team-oriented program is a difficult challenge
We use distributed POMDPs to analyze different allocations
of agents within a team-oriented program, and to suggest improvements to the program. The key innovation is to use
the distributed POMDP analysis not as a black box, but as
a glass box, offering insights into why particular allocations
lead to good or bad outcomes. These insights help to prune
the search space of different allocations, offering significant
speedups in the search. We present preliminary experimental
results to illustrate our methodology.},
	author = {Ranjit Nair and Tambe, Milind and Marsella, Stacy}
}
