an be used to abstract away from the physical reality by describing it as components that exist in discrete states with probabilistically invoked actions that change the state. The...
Duncan Gillies, David Thornley, Chatschik Bisdikia...
Inference in Markov Decision Processes has recently received interest as a means to infer goals of an observed action, policy recognition, and also as a tool to compute policies. ...
Software engineers tend to repeat mistakes when developing software. Automated static analysis tools can detect some of these mistakes early in the software process. However, thes...
The problem of making sequential decisions in unknown probabilistic environments is studied. In cycle t action yt results in perception xt and reward rt, where all quantities in g...
This paper integrates research in robot programming and reasoning about action with research in model-based reasoning about physical systems to provide a capability for modeling an...