In this article, we work towards the goal of developing agents that can learn to act in complex worlds. We develop a a new probabilistic planning rule representation to compactly ...
Hanna M. Pasula, Luke S. Zettlemoyer, Leslie Pack ...
Abstract. The paper describes a problem of multi-agent path planning in environment with obstacles. Novel approach to multi-agent optimal path planning, using graph representation ...
We present a bottom up algebraic approach for segmenting multiple 2D motion models directly from the partial derivatives of an image sequence. Our method fits a polynomial called ...
We view dynamic scheduling as a sequential decision problem. Firstly, we introduce a generalized planning operator, the stochastic task model (STM), which predicts the effects of ...
Abstract. We present a framework and algorithm for tracking articulated motion for humans. We use multiple calibrated cameras and an articulated human shape model. Tracking is perf...