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GECCO
2010
Springer
153views Optimization» more  GECCO 2010»
15 years 10 months ago
Multi-task evolutionary shaping without pre-specified representations
Shaping functions can be used in multi-task reinforcement learning (RL) to incorporate knowledge from previously experienced tasks to speed up learning on a new task. So far, rese...
Matthijs Snel, Shimon Whiteson
AIIDE
2008
15 years 9 months ago
A Cover-Based Approach to Multi-Agent Moving Target Pursuit
We explore the task of designing an efficient multi-agent system that is capable of capturing a single moving target, assuming that every agent knows the location of all agents on...
Alejandro Isaza, Jieshan Lu, Vadim Bulitko, Russel...
ATAL
2006
Springer
15 years 8 months ago
Evaluating bidding strategies for simultaneous auctions
Bidding for multiple items or bundles on online auctions raises challenging problems. We assume that an agent has a valuation function that returns its valuation for an arbitrary ...
Teddy Candale, Sandip Sen
DAGSTUHL
2008
15 years 8 months ago
Uniprocessor EDF Feasibility is an Integer Problem
The research on real-time scheduling has mostly focused on the development of algorithms that allows to test whether the constraints imposed on the task execution (often expressed ...
Enrico Bini
NIPS
2001
15 years 8 months ago
Variance Reduction Techniques for Gradient Estimates in Reinforcement Learning
Policy gradient methods for reinforcement learning avoid some of the undesirable properties of the value function approaches, such as policy degradation (Baxter and Bartlett, 2001...
Evan Greensmith, Peter L. Bartlett, Jonathan Baxte...