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» Negotiating Using Rewards
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FOCS
2003
IEEE
14 years 2 months ago
Approximation Algorithms for Orienteering and Discounted-Reward TSP
In this paper, we give the rst constant-factor approximationalgorithmfor the rooted Orienteering problem, as well as a new problem that we call the Discounted-Reward TSP, motivate...
Avrim Blum, Shuchi Chawla, David R. Karger, Terran...
ESAW
2004
Springer
14 years 2 months ago
Motivation-Based Selection of Negotiation Opponents
Abstract. If we are to enable agents to handle increasingly greater levels of complexity, it is necessary to equip them with mechanisms that support greater degrees of autonomy. Th...
Stephen J. Munroe, Michael Luck
ICML
2002
IEEE
14 years 9 months ago
Hierarchically Optimal Average Reward Reinforcement Learning
Two notions of optimality have been explored in previous work on hierarchical reinforcement learning (HRL): hierarchical optimality, or the optimal policy in the space defined by ...
Mohammad Ghavamzadeh, Sridhar Mahadevan
WEBI
2009
Springer
14 years 3 months ago
Zero-Sum Reward and Punishment Collaborative Filtering Recommendation Algorithm
In this paper, we propose a novel memory-based collaborative filtering recommendation algorithm. Our algorithm use a new metric named influence weight, which is adjusted with ze...
Nan Li, Chunping Li
ATAL
2010
Springer
13 years 10 months ago
Combining manual feedback with subsequent MDP reward signals for reinforcement learning
As learning agents move from research labs to the real world, it is increasingly important that human users, including those without programming skills, be able to teach agents de...
W. Bradley Knox, Peter Stone