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ROBOCUP
2007
Springer
153views Robotics» more  ROBOCUP 2007»
15 years 4 months ago
Model-Based Reinforcement Learning in a Complex Domain
Reinforcement learning is a paradigm under which an agent seeks to improve its policy by making learning updates based on the experiences it gathers through interaction with the en...
Shivaram Kalyanakrishnan, Peter Stone, Yaxin Liu
ICPR
2000
IEEE
15 years 2 months ago
Incremental Observable-Area Modeling for Cooperative Tracking
In this paper, we propose an observable-area model of the scene for real-time cooperative object tracking by multiple cameras. The knowledge of partners’ abilities is necessary ...
Norimichi Ukita, Takashi Matsuyama
AAAI
2010
14 years 11 months ago
Gaussian Mixture Model with Local Consistency
Gaussian Mixture Model (GMM) is one of the most popular data clustering methods which can be viewed as a linear combination of different Gaussian components. In GMM, each cluster ...
Jialu Liu, Deng Cai, Xiaofei He
COMPULOG
1999
Springer
15 years 2 months ago
Dynamic Constraint Models for Planning and Scheduling Problems
Planning and scheduling attracts an unceasing attention of computer science community. However, despite of similar character of both tasks, in most current systems planning and sch...
Roman Barták
IROS
2008
IEEE
98views Robotics» more  IROS 2008»
15 years 4 months ago
A scalable and distributed approach for self-assembly and self-healing of a differentiated shape
— As the ability to produce a large number of small, simple robotic agents improves, it becomes essential to control the behavior of these robots in such a way that the sum of th...
Michael Rubenstein, Wei-Min Shen