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ATAL
2010
Springer
15 years 7 months ago
Closing the learning-planning loop with predictive state representations
A central problem in artificial intelligence is to choose actions to maximize reward in a partially observable, uncertain environment. To do so, we must learn an accurate model of ...
Byron Boots, Sajid M. Siddiqi, Geoffrey J. Gordon
ATAL
2003
Springer
15 years 11 months ago
Cooperative negotiation for soft real-time distributed resource allocation
In this paper we present a cooperative negotiation protocol that solves a distributed resource allocation problem while conforming to soft real-time constraints in a dynamic envir...
Roger Mailler, Victor R. Lesser, Bryan Horling
IUI
2003
ACM
15 years 11 months ago
Towards more conversational and collaborative recommender systems
Current recommender systems, based on collaborative filtering, implement a rather limited model of interaction. These systems intelligently elicit information from a user only dur...
Giuseppe Carenini, Jocelyin Smith, David Poole
AIIDE
2006
15 years 7 months ago
Predicting User Physiological Response for Interactive Environments: An Inductive Approach
Affective reasoning holds great potential for interactive digital entertainment, education, and training. Incorporating affective reasoning into the decision-making capabilities o...
Scott W. McQuiggan, Sunyoung Lee, James C. Lester
AI
2000
Springer
15 years 6 months ago
Credal networks
Credal networks are models that extend Bayesian nets to deal with imprecision in probability, and can actually be regarded as sets of Bayesian nets. Evidence suggests that credal ...
Fabio Gagliardi Cozman