UNLABELLED Context plays a pivotal role in many decision-making scenarios, including social interactions wherein the identities and strategies of other decision makers often shape our behaviors. However, the neural mechanisms for tracking such contextual information are poorly understood. Here, we investigated how opponent identity affects human reinforcement learning during a simulated competi...

This thesis presents novel work on how to improve exploration in reinforcement learning using domain knowledge and knowledge-based approaches to reinforcement learning. It also identifies novel relationships between the algorithms’ and domains’ parameters and the exploration efficiency. The goal of solving reinforcement learning problems is to learn how to execute actions in order to maximise t...

BACKGROUND A long line of theoretical and empirical evidence implicates negative reinforcement as a process underlying the etiology and maintenance of risky alcohol use behaviors from adolescence through emerging adulthood. However, the bulk of this literature has relied on self-report measures, and there is a notable absence of behavioral modes of assessments of negative reinforcement-based al...

Reinforcement is an increase in premating reproductive isolation between taxa resulting from selection against hybrids. We present a model of reinforcement with a novel type of selection on female mating behavior. Previous models of reinforcement have focused on the divergence of female mating preferences between nascent species. We suggest that an increase in the level of female mating discrim...

BACKGROUND Negative reinforcement results in behavior to escape or avoid an aversive outcome. Withdrawal symptoms are purported to be negative reinforcers in perpetuating substance dependence, but little is known about negative reinforcement learning in this population. The purpose of this study was to examine reinforcement learning in substance dependent individuals (SDI), with an emphasis on ...

BACKGROUND Altered sensitivity to positive reinforcement has been hypothesized to contribute to the symptoms of attention-deficit hyperactivity disorder (ADHD). In this study, we evaluated the ability of children with and without ADHD to adapt their behavior to changing reinforcer availability. METHOD Of one hundred sixty-seven children, 97 diagnosed with ADHD completed a signal-detection tas...

Reinforcement-the process whereby maladaptive hybridization leads to the strengthening of prezygotic isolation between species-has a long history in the study of speciation. Because reinforcement affects traits involved in mate choice and fertility, it can have indirect effects on reproductive isolation between populations within species. Here we review examples of these "cascading effects of r...

The problem investigated in this paper is that of driving a car-like robot along a race track and the use of reinforcement learning to find a good control function. The reinforcement learner uses a case-based function approximator to extend the reinforcement learning paradigm to handle continuous states. The learned controller performs similar to the best control functions in both simulation an...

this article introduces the notions of functional space and concept as a way of knowledge representation and abstraction for reinforcement learning agents. these definitions are used as a tool of knowledge transfer among agents. the agents are assumed to be heterogeneous; they have different state spaces but share a same dynamic, reward and action space. in other words, the agents are assumed t...

in recent years, researches on reinforcement learning (rl) have focused on bridging the gap between adaptive optimal control and bio-inspired learning techniques. neural network reinforcement learning (nnrl) is among the most popular algorithms in the rl framework. the advantage of using neural networks enables the rl to search for optimal policies more efficiently in several real-life applicat...