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» Using the Electric Field Approach in the RoboCup Domain
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AAAI
2008
13 years 8 months ago
Feature Selection for Activity Recognition in Multi-Robot Domains
In multi-robot settings, activity recognition allows a robot to respond intelligently to the other robots in its environment. Conditional random fields are temporal models that ar...
Douglas L. Vail, Manuela M. Veloso
ROBOCUP
2004
Springer
117views Robotics» more  ROBOCUP 2004»
13 years 11 months ago
Map-Based Multiple Model Tracking of a Moving Object
In this paper we propose an approach for tracking a moving target using Rao-Blackwellised particle filters. Such filters represent posteriors over the target location by a mixtur...
Cody C. T. Kwok, Dieter Fox
ROBOCUP
2007
Springer
153views Robotics» more  ROBOCUP 2007»
13 years 12 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
GECCO
2010
Springer
184views Optimization» more  GECCO 2010»
13 years 10 months ago
Transfer learning through indirect encoding
An important goal for the generative and developmental systems (GDS) community is to show that GDS approaches can compete with more mainstream approaches in machine learning (ML)....
Phillip Verbancsics, Kenneth O. Stanley
ROBOCUP
2007
Springer
159views Robotics» more  ROBOCUP 2007»
13 years 12 months ago
High Accuracy Navigation in Unknown Environment Using Adaptive Control
Aiming to reduce cycle time and improving the accuracy on tracking, a modified adaptive control was developed, which adapts autonomously to changing dynamic parameters. The platfor...
Fernando Ribeiro, Ivo Moutinho, Nino Pereira, Fern...