We present a new approach for finding generalized contingent plans with loops and branches in situations where there is uncertainty in state properties and object quantities, but ...
Siddharth Srivastava, Neil Immerman, Shlomo Zilber...
— An important problem in robotics is planning and selecting actions for goal-directed behavior in noisy uncertain environments. The problem is typically addressed within the fra...
Markov decisionprocesses(MDPs) haveproven to be popular models for decision-theoretic planning, but standard dynamic programming algorithms for solving MDPs rely on explicit, stat...
An issue that is critical for the application of Markov decision processes MDPs to realistic problems is how the complexity of planning scales with the size of the MDP. In stochas...
In this paper we propose interaction-driven Markov games (IDMGs), a new model for multiagent decision making under uncertainty. IDMGs aim at describing multiagent decision problem...