Recent research in machine learning has focused on supervised induction for simple classi cation and reinforcement learning for simple reactive behaviors. In the process, the eld ...
We present an auction-based approach to manufacturing control. Workpieces auction off their current task, while machines bid for tasks. When awarding a machine, a workpiece takes ...
In this paper, we propose a stochastic version of a general purpose functional programming language as a method of modeling stochastic processes. The language contains random choi...
Withthe proliferationof software agents and smart hardware devices there is a growing realization that large-scale problems can be addressed by integration of such standalone syst...
When dealing with signals from complex environments, where multiple time-dependent signal signatures can interfere with each other in stochastically unpredictable ways, traditiona...
In this paper we focus on the problem of how infinite belief hierarchies can be represented and reasoned with in a computationally tractable way. When modeling nested beliefs one ...
We demonstrate how multiagent systems provide useful control techniques for modular self-reconfigurable (metamorphic) robots. Such robots consist of many modules that can move rel...