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ETS
2006
IEEE
118views Hardware» more  ETS 2006»
15 years 10 months ago
Living with Failure: Lessons from Nature?
- The resources available on a chip continue to grow, following Moore's Law. However, the major process by which the benefits of Moore's Law accrue, which is the continui...
Steve Furber
NIPS
1996
15 years 5 months ago
Multidimensional Triangulation and Interpolation for Reinforcement Learning
Dynamic Programming, Q-learning and other discrete Markov Decision Process solvers can be applied to continuous d-dimensional state-spaces by quantizing the state space into an arr...
Scott Davies
CP
2005
Springer
15 years 10 months ago
Planning and Scheduling to Minimize Tardiness
We combine mixed integer linear programming (MILP) and constraint programming (CP) to minimize tardiness in planning and scheduling. Tasks are allocated to facilities using MILP an...
John N. Hooker
CONSTRAINTS
2006
99views more  CONSTRAINTS 2006»
15 years 4 months ago
An Integrated Method for Planning and Scheduling to Minimize Tardiness
We combine mixed integer linear programming (MILP) and constraint programming (CP) to minimize tardiness in planning and scheduling. Tasks are allocated to facilities using MILP an...
John N. Hooker
ICCBR
2001
Springer
15 years 9 months ago
A Case-Based Reasoning View of Automated Collaborative Filtering
From some perspectives Automated Collaborative Filtering (ACF) appears quite similar to Case-Based Reasoning (CBR). It works on data organised around users and assets that might be...
Conor Hayes, Padraig Cunningham, Barry Smyth