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IJCAI
1989
13 years 8 months ago
Coping With Uncertainty in Map Learning
In many applications in mobile robotics, it is important for a robot to explore its environment in order to construct a representation of space useful for guiding movement. We refe...
Kenneth Basye, Thomas Dean, Jeffrey Scott Vitter
ICML
2010
IEEE
13 years 5 months ago
Constructing States for Reinforcement Learning
POMDPs are the models of choice for reinforcement learning (RL) tasks where the environment cannot be observed directly. In many applications we need to learn the POMDP structure ...
M. M. Hassan Mahmud
ICASSP
2009
IEEE
14 years 2 months ago
A semi-supervised learning approach to online audio background detection
We present a framework for audio background modeling of complex and unstructured audio environments. The determination of background audio is important for understanding and predi...
Selina Chu, Shrikanth S. Narayanan, C.-C. Jay Kuo
ICCV
2005
IEEE
14 years 1 months ago
A Study of Detecting Social Interaction with Sensors in a Nursing Home Environment
Social interaction plays an important role in our daily lives. It is one of the most important indicators of physical or mental diseases of aging patients. In this paper, we presen...
Datong Chen, Jie Yang, Howard D. Wactlar
AGENTS
1999
Springer
13 years 12 months ago
Team-Partitioned, Opaque-Transition Reinforcement Learning
In this paper, we present a novel multi-agent learning paradigm called team-partitioned, opaque-transition reinforcement learning (TPOT-RL). TPOT-RL introduces the concept of usin...
Peter Stone, Manuela M. Veloso