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The relationship between uncertainty and affect
Uncertainty and affect are fundamental and interrelated aspects of the human condition.
Uncertainty is often associated with negative affect, but in some circumstances, it is …
Uncertainty is often associated with negative affect, but in some circumstances, it is …
Modular deep reinforcement learning from reward and punishment for robot navigation
Abstract Modular Reinforcement Learning decomposes a monolithic task into several tasks
with sub-goals and learns each one in parallel to solve the original problem. Such learning …
with sub-goals and learns each one in parallel to solve the original problem. Such learning …
Reinforcement learning algorithms in global path planning for mobile robot
The paper is devoted to the research of two approaches for global path planning for mobile
robots, based on Q-Learning and Sarsa algorithms. The study has been done with different …
robots, based on Q-Learning and Sarsa algorithms. The study has been done with different …
[HTML][HTML] A 2D optimal path planning algorithm for autonomous underwater vehicle driving in unknown underwater canyons
This research aims to solve the safe navigation problem of autonomous underwater vehicles
(AUVs) in deep ocean, which is a complex and changeable environment with various …
(AUVs) in deep ocean, which is a complex and changeable environment with various …
Learning failure prevention skills for safe robot manipulation
Robots are more capable of achieving manipulation tasks for everyday activities than before.
However, the safety of manipulation skills that robots employ is still an open problem …
However, the safety of manipulation skills that robots employ is still an open problem …
Reward-punishment reinforcement learning with maximum entropy
We introduce the" soft Deep MaxPain"(softDMP) algorithm, which integrates the optimization
of long-term policy entropy into reward-punishment reinforcement learning objectives. Our …
of long-term policy entropy into reward-punishment reinforcement learning objectives. Our …
Improving robot motor learning with negatively valenced reinforcement signals
Both nociception and punishment signals have been used in robotics. However, the
potential for using these negatively valenced types of reinforcement learning signals for …
potential for using these negatively valenced types of reinforcement learning signals for …
Vicarious value learning: knowledge transfer through affective processing on a social differential outcomes task
The findings of differential outcomes training procedures in controlled stimulus-response
learning settings have been explained through theorizing two processes of response …
learning settings have been explained through theorizing two processes of response …
Bridging connectionism and relational cognition through bi-directional affective-associative processing
Connectionist architectures constitute a popular method for modelling animal associative
learning processes in order to glean insights into the formation of cognitive capacities. Such …
learning processes in order to glean insights into the formation of cognitive capacities. Such …
Affective-Associative Two-Process theory: A neural network investigation of adaptive behaviour in differential outcomes training
In this article we present a novel neural network implementation of Associative Two-Process
(ATP) theory based on an Actor–Critic-like architecture. Our implementation emphasizes the …
(ATP) theory based on an Actor–Critic-like architecture. Our implementation emphasizes the …