This article develops a stochastic programming framework for multiagent systems, where
task decomposition, assignment, and scheduling problems are simultaneously optimized …

We address the problem of situated temporal planning, in which an agent's plan can depend
on scheduled exogenous events, and thus it becomes important to take the passage of time …

Planning enables intelligent agents, such as robots, to act so as to achieve their long term
goals. To make the planning process tractable, a relatively low fidelity model of the world is …

Efficient sampling from constraint manifolds, and thereby generating a diverse set of
solutions for feasibility problems, is a fundamental challenge. We consider the case where a …

Making plans that depend on external events can be tricky. For example, an agent
considering a partial plan that involves taking a bus must recognize that this partial plan is …

Achieving an accurate model of the underwater domain that captures all its complex
dynamics represents a challenge. Therefore, planning solutions often involve replanning …

Agents that plan and act in the real world must deal with the fact that time passes as they are
planning. When timing is tight, there may be insufficient time to complete the search for a …

In online planning, search is concurrent with execution. Under the formulation of planning as
heuristic search, when a planner commits to an action, it re-roots its search tree at the node …

The problem of navigation among moving obstacles, sometimes referred to as SIPP, is a
problem in which the applicability of an action, such as moving to a particular neighboring …

In robot planning, tasks can often be achieved through multiple options, each consisting of
several actions. This work specifically addresses deadline constraints in task and motion …