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ATAL
2005
Springer
14 years 1 months ago
Improving reinforcement learning function approximators via neuroevolution
Reinforcement learning problems are commonly tackled with temporal difference methods, which use dynamic programming and statistical sampling to estimate the long-term value of ta...
Shimon Whiteson
GECCO
2007
Springer
217views Optimization» more  GECCO 2007»
13 years 9 months ago
A quantitative analysis of memory requirement and generalization performance for robotic tasks
In autonomous agent systems, memory is an important element to handle agent behaviors appropriately. We present the analysis of memory requirements for robotic tasks including wal...
DaeEun Kim
AAAI
2012
11 years 9 months ago
Learning from Demonstration for Goal-Driven Autonomy
Goal-driven autonomy (GDA) is a conceptual model for creating an autonomous agent that monitors a set of expectations during plan execution, detects when discrepancies occur, buil...
Ben George Weber, Michael Mateas, Arnav Jhala
WSC
2008
13 years 9 months ago
Multi-objective UAV mission planning using evolutionary computation
This investigation develops an innovative algorithm for multiple autonomous unmanned aerial vehicle (UAV) mission routing. The concept of a UAV Swarm Routing Problem (SRP) as a ne...
Adam J. Pohl, Gary B. Lamont
GECCO
2008
Springer
196views Optimization» more  GECCO 2008»
13 years 8 months ago
ADANN: automatic design of artificial neural networks
In this work an improvement of an initial approach to design Artificial Neural Networks to forecast Time Series is tackled, and the automatic process to design Artificial Neural N...
Juan Peralta, Germán Gutiérrez, Arac...