In attempting to address real-life decision problems, where uncertainty about input data prevails, some kind of representation of imprecise information is important and several ha...
Research in reinforcement learning has produced algorithms for optimal decision making under uncertainty that fall within two main types. The first employs a Bayesian framework, ...
Dynamic plan execution strategies allow an autonomous agent to respond to uncertainties while improving robustness and reducing the need for an overly conservative plan. Executive...
Patrick R. Conrad, Julie A. Shah, Brian C. William...
—We study the problem of actively searching for an object in a 3D environment under the constraint of a maximum search time, using a visually guided humanoid robot with twentysix...
Alexander Andreopoulos, Stephan Hasler, Heiko Wers...
We study the strategic behavior of risk-neutral non-myopic agents in Dynamic Parimutuel Markets (DPM). In a DPM, agents buy or sell shares of contracts, whose future payoff in a p...