We present metric?? , a provably near-optimal algorithm for reinforcement learning in Markov decision processes in which there is a natural metric on the state space that allows t...
We propose an informative dialect recognition system that learns phonetic transformation rules, and uses them to identify dialects. A hidden Markov model is used to align referenc...
Nancy F. Chen, Wade Shen, Joseph P. Campbell, Pedr...
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...
Revelation policies in an e-marketplace differ in terms of the level of competitive information disseminated to participating sellers. Since sellers who repeatedly compete against...
Amy R. Greenwald, Karthik Kannan, Ramayya Krishnan
In sequential decision making under uncertainty, as in many other modeling endeavors, researchers observe a dynamical system and collect data measuring its behavior over time. The...