Task Transfer by Preference-Based Cost Learning

The goal of task transfer in reinforcement learning is migrating the action policy of an agent to the target task from the source task. Given their successes on robotic action planning, current methods mostly rely on two requirements: exactly-relevant expert demonstrations or the explicitly-coded cost function on target task, both of which, however, are inconvenient to obtain in practice. In this paper, we relax these two strong conditions by developing a novel task transfer framework where the expert preference is applied as a guidance. In particular, we alternate the following two steps: Firstly, letting experts apply pre-defined preference rules to select related expert demonstrates for the target task. Secondly, based on the selection result, we learn the target cost function and trajectory distribution simultaneously via enhanced Adversarial MaxEnt IRL and generate more trajectories by the learned target distribution for the next preference selection. The theoretical analysis on the distribution learning and convergence of the proposed algorithm are provided. Extensive simulations on several benchmarks have been conducted for further verifying the effectiveness of the proposed method.Comment: Accepted to AAAI 2019. Mingxuan Jing and Xiaojian Ma contributed equally to this wor

Engaging low skilled employees in workplace learning : UK Commission for Employment and Skills Evidence Report no. 43

The Employee Demand study (UKCES, 2009) highlighted the significant barriers to learning that are faced by a number of UK employees. This report sets out the findings of a study into the motivators and barriers to participation in workplace learning by low skilled employees. Employees in low skilled jobs are a group which has been overlooked in previous research. The study was carried out by the Employment Research Institute (ERI) at Edinburgh Napier University on behalf of the UK Commission for Employment and Skills (the UK Commission). The report presents the results of a survey of both employee and employer views on participation in workplace learning in the care sector in north east England and the hotel sector in Yorkshire and Humberside. As well as a standard survey, the report also outlines the stated preference approach adopted. The stated preference approach allows employees to consider a hypothetical case of participation in workplace learning. Employees were given choices of combinations of job and learning related factors that might affect their preference for or against workplace learning. In conclusion, the report suggests many positive features which employers, individuals and policy makers could build on in developing the skills of people in low skilled jobs, which is important in securing our competitive advantage in the long term

Dorsal-CA1 hippocampal neuronal ensembles encode nicotine-reward contextual associations

Natural and drug rewards increase the motivational valence of stimuli in the environment that, through Pavlovian learning mechanisms, become conditioned stimuli that directly motivate behavior in the absence of the original unconditioned stimulus. While the hippocampus has received extensive attention for its role in learning and memory processes, less is known regarding its role in drug-reward associations. We used in vivo Ca2+ imaging in freely moving mice during the formation of nicotine preference behavior to examine the role of the dorsal-CA1 region of the hippocampus in encoding contextual reward-seeking behavior. We show the development of specific neuronal ensembles whose activity encodes nicotine-reward contextual memories and that are necessary for the expression of place preference. Our findings increase our understanding of CA1 hippocampal function in general and as it relates to reward processing by identifying a critical role for CA1 neuronal ensembles in nicotine place preference

The design and implementation of an adaptive e-learning system

This paper describes the design and implementation of an adaptive e-learning system that provides a template for different learning materials as well as a student model that incorporates five distinct student characteristics as an aid to learning: primary characteristics are prior knowledge, learning style and the presence or absence of animated multimedia aids (multimedia mode); secondary characteristics include page background preference and link colour preference. The use of multimedia artefacts as a student characteristic has not previously been implemented or evaluated. The system development consists of a requirements analysis, design and implementation. The design models including use case diagrams, conceptual design, sequence diagrams, navigation design and presentation design are expressed using Unified Modelling Language (UML). The adaptive e-learning system was developed in a template implemented using Java Servlets, XHTML, XML, JavaScript and HTML. The template is a domain-independent adaptive e-learning system that has functions of both adaptivity and adaptability