Reward-based selection

Reward-based selection is a technique used in evolutionary algorithms for selecting potentially useful solutions for recombination. The probability… (More)
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Topic mentions per year

Topic mentions per year

2003-2017
0120032017

Papers overview

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2017
2017
The multi-armed bandit problem forms the foundation for solving a wide range of on-line stochastic optimization problems through… (More)
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Review
2015
Review
2015
The generation of motion for robots and mobile manipulators in unstructured, dynamic environments has been a key research topic… (More)
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2014
2014
Is it possible for neural responses to others' rewards to be as strong as those for the self? Although prior fMRI studies have… (More)
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Review
2014
Review
2014
Each employee’s performance is important in an organization. A way to motivate it is through the application of reinforcement… (More)
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2014
2014
Multi-objectivization is the process of transforming a single objective problem into a multi-objective problem. Research in… (More)
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2013
2013
This paper investigates the impact of reward shaping on a reinforcement learning-based spoken dialogue system’s learning. A… (More)
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2009
2009
Reinforcement learning suffers scalability problems due to the state space explosion and the temporal credit assignment problem… (More)
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2007
2007
Recent research provides new insights into amygdala contributions to positive emotion and reward. Studies of neuronal activity in… (More)
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Highly Cited
2003
Highly Cited
2003
Shaping has proven to be a powerful but precarious means of improving reinforcement learning performance. Ng, Harada, and Russell… (More)
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