This paper extends the framework of partially observable Markov decision processes (POMDPs) to multi-agent settings by incorporating the notion of agent models into the state spac...
The success of stochastic algorithms is often due to their ability to effectively amplify the performance of search heuristics. This is certainly the case with stochastic sampling ...
To reason effectively about programs, it is important to have some version of a transitive-closure operator so that we can describe such notions as the set of nodes reachable from ...
Neil Immerman, Alexander Moshe Rabinovich, Thomas ...
This paper proposes a system for model based human motion estimation. We start with a human model generation system, which uses a set of input images to automatically generate a f...
Attempts to use finite models to guide the search for proofs by resolution and the like in first order logic all suffer from the need to trade off the expense of generating and m...