Fermionic Molecular Dynamics for nuclear dynamics and thermodynamics

A new Fermionic Molecular Dynamics (FMD) model based on a Skyrme functional is proposed in this paper. After introducing the basic formalism, some first applications to nuclear structure and nuclear thermodynamics are presentedComment: 5 pages, Proceedings of the French-Japanese Symposium, September 2008. To be published in Int. J. of Mod. Phys.

Explaining the Fixed Cost Component of Discounting: The Importance of Students\u27 Liquidity Constraints

Utilizing experimental data on choices over real monetary rewards made by university students, we provide evidence that two measures of liquidity, income and employment status, significantly explain differences in patterns of discounting. We find an average fixed cost component of discounting in the range of $5 for unemployed students and near$0 for employed students. An increase in annual disposable income of $1000 decreases the fixed cost component of discounting by approximately$0.20 to $0.25. These findings can help resolve the puzzle that some studies in the literature find evidence of present-bias and magnitude effects and some do not

High temporal discounters overvalue immediate rewards rather than undervalue future rewards : an event-related brain potential study

Impulsivity is characterized in part by heightened sensitivity to immediate relative to future rewards. Although previous research has suggested that "high discounters" in intertemporal choice tasks tend to prefer immediate over future rewards because they devalue the latter, it remains possible that they instead overvalue immediate rewards. To investigate this question, we recorded the reward positivity, a component of the event-related brain potential (ERP) associated with reward processing, with participants engaged in a task in which they received both immediate and future rewards and nonrewards. The participants also completed a temporal discounting task without ERP recording. We found that immediate but not future rewards elicited the reward positivity. High discounters also produced larger reward positivities to immediate rewards than did low discounters, indicating that high discounters relatively overvalued immediate rewards. These findings suggest that high discounters may be more motivated than low discounters to work for monetary rewards, irrespective of the time of arrival of the incentives

Reinforcement Learning for Racecar Control

This thesis investigates the use of reinforcement learning to learn to drive a racecar in the simulated environment of the Robot Automobile Racing Simulator. Real-life race driving is known to be difficult for humans, and expert human drivers use complex sequences of actions. There are a large number of variables, some of which change stochastically and all of which may affect the outcome. This makes driving a promising domain for testing and developing Machine Learning techniques that have the potential to be robust enough to work in the real world. Therefore the principles of the algorithms from this work may be applicable to a range of problems. The investigation starts by finding a suitable data structure to represent the information learnt. This is tested using supervised learning. Reinforcement learning is added and roughly tuned, and the supervised learning is then removed. A simple tabular representation is found satisfactory, and this avoids difficulties with more complex methods and allows the investigation to concentrate on the essentials of learning. Various reward sources are tested and a combination of three are found to produce the best performance. Exploration of the problem space is investigated. Results show exploration is essential but controlling how much is done is also important. It turns out the learning episodes need to be very long and because of this the task needs to be treated as continuous by using discounting to limit the size of the variables stored. Eligibility traces are used with success to make the learning more efficient. The tabular representation is made more compact by hashing and more accurate by using smaller buckets. This slows the learning but produces better driving. The improvement given by a rough form of generalisation indicates the replacement of the tabular method by a function approximator is warranted. These results show reinforcement learning can work within the Robot Automobile Racing Simulator, and lay the foundations for building a more efficient and competitive agent

A general theory of intertemporal decision-making and the perception of time

Animals and humans make decisions based on their expected outcomes. Since relevant outcomes are often delayed, perceiving delays and choosing between earlier versus later rewards (intertemporal decision-making) is an essential component of animal behavior. The myriad observations made in experiments studying intertemporal decision-making and time perception have not yet been rationalized within a single theory. Here we present a theory-Training--Integrated Maximized Estimation of Reinforcement Rate (TIMERR)--that explains a wide variety of behavioral observations made in intertemporal decision-making and the perception of time. Our theory postulates that animals make intertemporal choices to optimize expected reward rates over a limited temporal window; this window includes a past integration interval (over which experienced reward rate is estimated) and the expected delay to future reward. Using this theory, we derive a mathematical expression for the subjective representation of time. A unique contribution of our work is in finding that the past integration interval directly determines the steepness of temporal discounting and the nonlinearity of time perception. In so doing, our theory provides a single framework to understand both intertemporal decision-making and time perception.Comment: 37 pages, 4 main figures, 3 supplementary figure

Impulsivity, Rejection Sensitivity, and Reactions to Stressors in Borderline Personality Disorder

This research investigated baseline impulsivity, rejection sensitivity, and reactions to stressors in individuals with borderline personality disorder compared to healthy individuals and those with avoidant personality disorder . The borderline group showed greater impulsivity than the avoidant and healthy groups both in a delay-discounting task with real monetary rewards and in self-reported reactions to stressors; moreover, these findings could not be explained by co-occurring substance use disorders. Distress reactions to stressors were equally elevated in both personality disorder groups (relative to the healthy group). The borderline and avoidant groups also reported more maladaptive reactions to a stressor of an interpersonal versus non-interpersonal nature, whereas the healthy group did not. Finally, self-reported impulsive reactions to stressors were associated with baseline impulsivity in the delay-discounting task, and greater self-reported reactivity to interpersonal than non-interpersonal stressors was associated with rejection sensitivity. This research highlights distinct vulnerabilities contributing to impulsive behavior in borderline personality disorder