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AAAI
2007
11 years 3 months ago
Modeling and Learning Vague Event Durations for Temporal Reasoning
This paper reports on our recent work on modeling and automatically extracting vague, implicit event durations from text (Pan et al., 2006a, 2006b). It is a kind of commonsense kn...
Feng Pan, Rutu Mulkar, Jerry R. Hobbs
AAAI
2007
11 years 3 months ago
A Modular Action Description Language for Protocol Composition
Protocols are modular abstractions that capture patterns of interaction among agents. The compelling vision behind protocols is to enable creating customized interactions by refi...
Nirmit Desai, Munindar P. Singh
AAAI
2007
11 years 3 months ago
An Integrated Robotic System for Spatial Understanding and Situated Interaction in Indoor Environments
A major challenge in robotics and artificial intelligence lies in creating robots that are to cooperate with people in human-populated environments, e.g. for domestic assistance ...
Hendrik Zender, Patric Jensfelt, Óscar Mart...
AAAI
2007
11 years 3 months ago
PhotoSlap: A Multi-player Online Game for Semantic Annotation
Multimedia content presents special challenges for the search engines, and could benefit from semantic annotation of images. Unfortunately, manual labeling is too tedious and tim...
Chien-Ju Ho, Tsung-Hsiang Chang, Jane Yung-jen Hsu
AAAI
2007
11 years 3 months ago
Diagnosis of Discrete-Event Systems Using Satisfiability Algorithms
Alban Grastien, Anbulagan, Jussi Rintanen, Elena K...
AAAI
2007
11 years 3 months ago
Real-Time Identification of Operating Room State from Video
Beenish Bhatia, Tim Oates, Yan Xiao, Peter Fu-Ming...
AAAI
2007
11 years 3 months ago
Authorial Idioms for Target Distributions in TTD-MDPs
In designing Markov Decision Processes (MDP), one must define the world, its dynamics, a set of actions, and a reward function. MDPs are often applied in situations where there i...
David L. Roberts, Sooraj Bhat, Kenneth St. Clair, ...
AAAI
2007
11 years 3 months ago
Temporal Difference and Policy Search Methods for Reinforcement Learning: An Empirical Comparison
Reinforcement learning (RL) methods have become popular in recent years because of their ability to solve complex tasks with minimal feedback. Both genetic algorithms (GAs) and te...
Matthew E. Taylor, Shimon Whiteson, Peter Stone
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