We contribute an approach for interactive policy learning through expert demonstration that allows an agent to actively request and effectively represent demonstration examples. I...
In this paper we study the topic of CBR systems learning from observations in which those observations can be represented as stochastic policies. We describe a general framework wh...
Kellen Gillespie, Justin Karneeb, Stephen Lee-Urba...
The paper describes main features of an Intelligent Scheduler for Road Transportation Applications based on Magenta agent technology and characterized by a number of unique, advan...
This paper describes an agent-based platform for the allocation of loads in distributed transportation logistics, developed as a collaboration between CWI, Dutch National Center f...
Muskens presents in Meaning and Partiality a semantics of possibly contradictory beliefs and other propositional attitudes. We propose a different partial logic based on a few key...