In this work we present a methodology for intelligent path planning in an uncertain environment using vision like sensors, i.e., sensors that allow the sensing of the environment ...
—This paper introduces a new algorithm for probabilistic motion planning in arbitrary, uncertain vector fields, with emphasis on high-level planning for Montgolfier´e balloons...
Michael T. Wolf, Lars Blackmore, Yoshiaki Kuwata, ...
We introduce a class of learning problems where the agent is presented with a series of tasks. Intuitively, if there is relation among those tasks, then the information gained duri...
Abstract. This paper proposes an entropy based Markov chain (EMC) fusion technique and demonstrates its applications in multisensor fusion. Self-entropy and conditional entropy, wh...
We propose a new decision-theoretic approach for solving execution-time deliberation scheduling problems using recent advances in Generalized Semi-Markov Decision Processes (GSMDP...