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» Agent and Task Modeling at Honeywell
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AICOM
2002
103views more  AICOM 2002»
14 years 9 months ago
The emergent computational potential of evolving artificial living systems
The computational potential of artificial living systems can be studied without knowing the algorithms that govern their behavior. Modeling single organisms by means of socalled c...
Jirí Wiedermann, Jan van Leeuwen
ATAL
2007
Springer
15 years 3 months ago
Model-based function approximation in reinforcement learning
Reinforcement learning promises a generic method for adapting agents to arbitrary tasks in arbitrary stochastic environments, but applying it to new real-world problems remains di...
Nicholas K. Jong, Peter Stone
AAAI
2008
14 years 12 months ago
CIGAR: Concurrent and Interleaving Goal and Activity Recognition
In artificial intelligence and pervasive computing research, inferring users' high-level goals from activity sequences is an important task. A major challenge in goal recogni...
Derek Hao Hu, Qiang Yang
71
Voted
IAT
2003
IEEE
15 years 2 months ago
Problem-solving in open environments
With the increasing use of the internet, many problemsolving tasks such as resource allocation, scheduling, planning, and configuration pose themselves in an open setting involvi...
Santiago Macho-Gonzalez, Boi Faltings
COOPIS
2002
IEEE
15 years 2 months ago
Formal Ontology Engineering in the DOGMA Approach
This paper presents a specifically database-inspired approach (called DOGMA) for engineering formal ontologies, implemented as shared resources used to express agreed formal semant...
Mustafa Jarrar, Robert Meersman