We develop a new graphical representation for interactive partially observable Markov decision processes (I-POMDPs) that is significantly more transparent and semantically clear t...
We present a method for transforming the infinite interactive state space of interactive POMDPs (I-POMDPs) into a finite one, thereby enabling the computation of exact solutions. ...
Abstract— Research on numerical solution methods for partially observable Markov decision processes (POMDPs) has primarily focused on discrete-state models, and these algorithms ...
In order to interact successfully in social situations, a robot must be able to observe others' actions and base its own behavior on its beliefs about their intentions. Many ...
Decentralized partially observable MDPs (DEC-POMDPs) provide a rich framework for modeling decision making by a team of agents. Despite rapid progress in this area, the limited sc...