Reinforcement learning problems are commonly tackled with temporal difference methods, which use dynamic programming and statistical sampling to estimate the long-term value of ta...
Web searchers reformulate their queries, as they adapt to search engine behavior, learn more about a topic, or simply correct typing errors. Automatic query rewriting can help user...
Rosie Jones, Kevin Bartz, Pero Subasic, Benjamin R...
We present an architectural approach to learning problem solving skills from demonstration, using internal models to represent problem-solving operational knowledge. Internal forwa...
Haris Dindo, Antonio Chella, Giuseppe La Tona, Mon...
Game theoretic modeling and equilibrium analysis of congestion games have provided insights in the performance of Internet congestion control, road transportation networks, etc. D...
We address the learning of trust based on past observations and context information. We argue that from the truster's point of view trust is best expressed as one of several ...