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AGENTS
2001
Springer
14 years 2 months ago
Using background knowledge to speed reinforcement learning in physical agents
This paper describes Icarus, an agent architecture that embeds a hierarchical reinforcement learning algorithm within a language for specifying agent behavior. An Icarus program e...
Daniel G. Shapiro, Pat Langley, Ross D. Shachter
AAAI
2008
14 years 4 days ago
Memetic Networks: Analyzing the Effects of Network Properties in Multi-Agent Performance
We explore the relationship between properties of the network defined by connected agents and the global system performance. This is achieved by means of a novel class of optimiza...
Ricardo M. Araujo, Luís C. Lamb
NIPS
1993
13 years 11 months ago
Robust Reinforcement Learning in Motion Planning
While exploring to nd better solutions, an agent performing online reinforcement learning (RL) can perform worse than is acceptable. In some cases, exploration might have unsafe, ...
Satinder P. Singh, Andrew G. Barto, Roderic A. Gru...
GECCO
2006
Springer
185views Optimization» more  GECCO 2006»
14 years 1 months ago
Memory analysis and significance test for agent behaviours
Many agent problems in a grid world have a restricted sensory information and motor actions. The environmental conditions need dynamic processing of internal memory. In this paper...
DaeEun Kim
MIS
2008
Springer
149views Multimedia» more  MIS 2008»
13 years 9 months ago
Home-Explorer: Ontology-based physical artifact search and hidden object detection system
A new system named Home-Explorer that searches and finds physical artifacts in a smart indoor environment is proposed. The view on which it is based is artifact-centered and uses s...
Bin Guo, Satoru Satake, Michita Imai