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AAAI
2008
13 years 10 months ago
Achieving Far Transfer in an Integrated Cognitive Architecture
Transfer is the ability to employ knowledge acquired in one task to improve performance in another. We study transfer in the context of the ICARUS cognitive architecture, which su...
Dan Shapiro, Tolga Könik, Paul O'Rorke
ATAL
2007
Springer
14 years 1 months ago
Multiagent reinforcement learning and self-organization in a network of agents
To cope with large scale, agents are usually organized in a network such that an agent interacts only with its immediate neighbors in the network. Reinforcement learning technique...
Sherief Abdallah, Victor R. Lesser
AAAI
2012
11 years 10 months ago
Discovering Constraints for Inductive Process Modeling
Scientists use two forms of knowledge in the construction of explanatory models: generalized entities and processes that relate them; and constraints that specify acceptable combi...
Ljupco Todorovski, Will Bridewell, Pat Langley
PKDD
2010
Springer
212views Data Mining» more  PKDD 2010»
13 years 6 months ago
Cross Validation Framework to Choose amongst Models and Datasets for Transfer Learning
Abstract. One solution to the lack of label problem is to exploit transfer learning, whereby one acquires knowledge from source-domains to improve the learning performance in the t...
ErHeng Zhong, Wei Fan, Qiang Yang, Olivier Versche...
AGENTS
1999
Springer
13 years 12 months ago
Team-Partitioned, Opaque-Transition Reinforcement Learning
In this paper, we present a novel multi-agent learning paradigm called team-partitioned, opaque-transition reinforcement learning (TPOT-RL). TPOT-RL introduces the concept of usin...
Peter Stone, Manuela M. Veloso