To design a stochastic simulation experiment, it is helpful to have an estimate of the simulation run lengths required to achieve desired statistical precision. Preliminary estima...
This paper presents a model of neural network embodiment of intentions and planning mechanisms for autonomous agents. The model bridges the dichotomy of symbolic and non-symbolic ...
Probabilistic relational models are an efficient way to learn and represent the dynamics in realistic environments consisting of many objects. Autonomous intelligent agents that gr...
We consider the problem of cooperative multiagent planning under uncertainty, formalized as a decentralized partially observable Markov decision process (Dec-POMDP). Unfortunately...
Matthijs T. J. Spaan, Frans A. Oliehoek, Nikos A. ...
An "inconsistent" particle filter produces--in a statistical sense--larger estimation errors than predicted by the model on which the filter is based. Two test variables ...