This work addresses the problem of efficiently learning action schemas using a bounded number of samples (interactions with the environment). We consider schemas in two languages-...
— A central goal of robotics and AI is to be able to deploy an agent to act autonomously in the real world over an extended period of time. To operate in the real world, autonomo...
A central problem in artificial intelligence is to choose actions to maximize reward in a partially observable, uncertain environment. To do so, we must learn an accurate model of ...
An Autonomous Science Agent has been flying onboard the Earth Observing One Spacecraft since 2003. This software enables the spacecraft to autonomously detect and responds to scie...
Steve A. Chien, Rob Sherwood, Daniel Tran, Benjami...
Abstract. This paper deals with the issue of learning in multi-agent systems (MAS). Particularly, we are interested in BDI (Belief, Desire, Intention) agents. Despite the relevance...