The ways in which an agent’s actions affect the world can often be modeled compactly using a set of relational probabilistic planning rules. This paper addresses the problem of ...
Ashwin Deshpande, Brian Milch, Luke S. Zettlemoyer...
In this paper, we introduce the notion of communication channel into a multiagent system. We formalize the system in term of logic with Belief modality, where each possible world i...
In this paper, we discuss how to test partially specified IOTS through lossless queues. A liberal assumption is made of the IOTS model by allowing both blocked and unspecified inpu...
Filtering denotes any method whereby an agent updates its belief state—its knowledge of the state of the world—from a sequence of actions and observations. In logical filterin...
The problem of reinforcement learning in large factored Markov decision processes is explored. The Q-value of a state-action pair is approximated by the free energy of a product o...