Reinforcement Learning Theory (RLT) provides a powerful framework for understanding and precisely modelling learning16. In RLT, prediction errors signal the unexpectedness of outcomes and affect the choices we make in the future. The influence that prediction errors have on choices can be modelled indi...
Overactive behavioral approach motivation tendencies are among these proposed causal pathways and are addressed within Reinforcement Sensitivity Theory (RST). RST proposes that overactive behavioral approach tendencies are associated with over responsiveness to immediately reinforcing stimuli and result from an...
Reinforcement Sensitivity Theory (RST) is composed of two main components: (a) a state description of neural systems and associated, relatively short-term,... P Corr,N Mcnaughton 被引量: 0发表: 2007年 Reinforcement sensitivity theory and personality. A fully fledged neuroscience of personality is...
There is considerable interest in Gray's reinforcement sensitivity theory. However, few measures of the behavioral approach (BAS) and inhibition systems (BIS) exist for children. Moreover, the theory was substantially revised a decade ago and measurement instruments are still largely based on the ol...
RL algorithms also deploy a fair bit of game-theory mathematics and strategies, as well. The first two elements in any RL model are the environment and the agent. Using the example of a game of chess, the environment is the game board and the agent is the player. The s...
An hypothesis was tested which predicted the effect on two-choice, visual discrimination learning of four stimulus conditions associated with reward. The hypothesis was based on the theory that stimuli associated with reward operate as (... J Denegre - 《Journal of Experimental Child Psychology》 ...
Reinforcement learning is also used in operations research, information theory, game theory, control theory, simulation-based optimization, multi-agent systems, swarm intelligence, statistics, genetic algorithms and ongoing industrial automation efforts. ...
Flexible job-shop scheduling problem (FJSP), covering operation research, sequencing theory, and optimization methods, is mainly to determine the processing equipment and process path planning. It is one of the hot topics in the scheduling system2. Especially, flexible double shop scheduling problem ...
Using theory-driven qualitative patterns of activation as well as a quantitative model comparison exercise, our neuro-imaging analyses then revealed a functional dissociation. On the one hand, neural activity in the negative prefrontal network (i.e., DMPFC and DLPFC) correlated with a condition-...
The quantum compilation is a fundamental problem in the quantum computation theory, consisting of approximating any unitary transformation as a finite sequence of unitary operators Aj is chosen from a universal set of gates \({{{\mathcal{B}}}\). In this work, we ask the agent to approximate...