We present a decision making algorithm for agents that act in partially observable domains which they do not know fully. Making intelligent choices in such domains is very difficu...
This paper describes SiN, a novel case-based planning algorithm that combines conversational case retrieval with generative planning. SiN is provably correct, and can generate pla...
In timed, zero-sum games, the goal is to maximize the probability of winning, which is not necessarily the same as maximizing our expected reward. We consider cumulative intermedi...
Intelligent agents acting in real world environments need to synthesize their course of action based on multiple sources of knowledge. They also need to generate plans that smoothl...
Multiagent environments are often highly dynamic and only partially observable which makes deliberative action planning computationally hard. In many such environments, however, a...