We present a new approach for finding generalized contingent plans with loops and branches in situations where there is uncertainty in state properties and object quantities, but ...
Siddharth Srivastava, Neil Immerman, Shlomo Zilber...
One of the most challenging aspects of reasoning, planning, and acting in a multi-agent domain is reasoning about what the agents know about the knowledge of their fellows, and to...
Chitta Baral, Gregory Gelfond, Tran Cao Son, Enric...
In this paper we investigate updates of knowledge bases represented by logic programs. In order to represent negative information, we use generalized logic programs which allow de...
Interactions between agents in an open system such as the Internet require a significant degree of flexibility. A crucial aspect of the development of such methods is the notion o...
In this chapter, we describe a view of statistical learning in the inductive logic programming setting based on kernel methods. The relational representation of data and background...