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» Models for Representing Task Ontologies
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CEC
2005
IEEE
14 years 12 months ago
Co-evolutionary modular neural networks for automatic problem decomposition
Abstract- Decomposing a complex computational problem into sub-problems, which are computationally simpler to solve individually and which can be combined to produce a solution to ...
Vineet R. Khare, Xin Yao, Bernhard Sendhoff, Yaoch...
ICCAD
2004
IEEE
125views Hardware» more  ICCAD 2004»
15 years 6 months ago
Temporal floorplanning using the T-tree formulation
Improving logic capacity by time-sharing, dynamically reconfigurable FPGAs are employed to handle designs of high complexity and functionality. In this paper, we model each task ...
Ping-Hung Yuh, Chia-Lin Yang, Yao-Wen Chang
LAMAS
2005
Springer
15 years 3 months ago
Multi-agent Relational Reinforcement Learning
In this paper we report on using a relational state space in multi-agent reinforcement learning. There is growing evidence in the Reinforcement Learning research community that a r...
Tom Croonenborghs, Karl Tuyls, Jan Ramon, Maurice ...
AAAI
2007
15 years 8 days ago
Measuring the Level of Transfer Learning by an AP Physics Problem-Solver
Transfer learning is the ability of an agent to apply knowledge learned in previous tasks to new problems or domains. We approach this problem by focusing on model formulation, i....
Matthew Klenk, Kenneth D. Forbus
EMNLP
2010
14 years 8 months ago
Measuring Distributional Similarity in Context
The computation of meaning similarity as operationalized by vector-based models has found widespread use in many tasks ranging from the acquisition of synonyms and paraphrases to ...
Georgiana Dinu, Mirella Lapata