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Reward

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Exploring the Black Box of Managing Total Rewards for Older Professionals in the Canadian Financial Services Sector.

Canadian journal on aging = La revue canadienne du vieillissement
This study extends our knowledge about the management of older employees in the sector of financial services, which faces enormous transformational pressures (e.g., emergence of artificial intelligence, digital services). Based on the black box model...

An approach to solving optimal control problems of nonlinear systems by introducing detail-reward mechanism in deep reinforcement learning.

Mathematical biosciences and engineering : MBE
In recent years, dynamic programming and reinforcement learning theory have been widely used to solve the nonlinear control system (NCS). Among them, many achievements have been made in the construction of network model and system stability analysis,...

Generalized Single-Vehicle-Based Graph Reinforcement Learning for Decision-Making in Autonomous Driving.

Sensors (Basel, Switzerland)
In the autonomous driving process, the decision-making system is mainly used to provide macro-control instructions based on the information captured by the sensing system. Learning-based algorithms have apparent advantages in information processing a...

Sharing Rewards Undermines Coordinated Hunting.

Journal of computational biology : a journal of computational molecular cell biology
Coordinated hunting is widely observed in animals, and sharing rewards is often considered a major incentive for its success. While current theories about the role played by sharing in coordinated hunting are based on correlational evidence, we revea...

Application of Deep Reinforcement Learning to NS-SHAFT Game Signal Control.

Sensors (Basel, Switzerland)
Reinforcement learning (RL) with both exploration and exploit abilities is applied to games to demonstrate that it can surpass human performance. This paper mainly applies Deep Q-Network (DQN), which combines reinforcement learning and deep learning ...

Value-free random exploration is linked to impulsivity.

Nature communications
Deciding whether to forgo a good choice in favour of exploring a potentially more rewarding alternative is one of the most challenging arbitrations both in human reasoning and in artificial intelligence. Humans show substantial variability in their e...

Socially situated artificial intelligence enables learning from human interaction.

Proceedings of the National Academy of Sciences of the United States of America
Regardless of how much data artificial intelligence agents have available, agents will inevitably encounter previously unseen situations in real-world deployments. Reacting to novel situations by acquiring new information from other people-socially s...

Flexible control as surrogate reward or dynamic reward maximization.

Cognition
The utility of a given experience, like interacting with a particular friend or tasting a particular food, fluctuates continually according to homeostatic and hedonic principles. Consequently, to maximize reward, an individual must be able to escape ...

The Influence of Robots' Fairness on Humans' Reward-Punishment Behaviors and Trust in Human-Robot Cooperative Teams.

Human factors
OBJECTIVE: Based on social exchange theory, this study investigates the effects of robots' fairness and social status on humans' reward-punishment behaviors and trust in human-robot interactions.

Memristor Neural Network Circuit Based on Operant Conditioning With Immediacy and Satiety.

IEEE transactions on biomedical circuits and systems
Most of the operant conditioning only consider the basic theory, but the influencing factors such as immediacy and satiety are ignored. In this paper, a memristor neural network circuit based on operant conditioning with immediacy and satiety is prop...