Learning to Follow Instructions in Text-Based Games

Text-based games present a unique class of sequential decision making problem in which agents interact with a partially observable, simulated environment via actions and observations conveyed through natural language. Such observations typically include instructions that, in a reinforcement learning (RL) setting, can directly or indirectly guide a player towards completing reward-worthy tasks. In this work, we study the ability of RL agents to follow such instructions. We conduct experiments that show that the performance of state-of-the-art text-based game agents is largely unaffected by the presence or absence of such instructions, and that these agents are typically unable to execute tasks to completion. To further study and address the task of instruction following, we equip RL agents with an internal structured representation of natural language instructions in the form of Linear Temporal Logic (LTL), a formal language that is increasingly used for temporally extended reward specification in RL. Our framework both supports and highlights the benefit of understanding the temporal semantics of instructions and in measuring progress towards achievement of such a temporally extended behaviour. Experiments with 500+ games in TextWorld demonstrate the superior performance of our approach.Comment: NeurIPS 202

The virtue of customising solutions: A managerial framework

Solutions are commonly viewed as an integrated bundle of products and services. The solutions also need to be adapted to the specific demands of individual customers, resulting in a high degree of customisation. At the same time, manufacturers offering solutions are guided by strict demands regarding productivity and economies of scale, which, at least partly, are enabled by a higher degree of standardisation. Hence, manufacturing firms have to balance internal demands for efficiency with demands for customisation of solutions. To guide firms concerned with this challenge, a managerial framework for customisation of solutions based on commonalities is proposed

Analysis of mode distribution for PMMA Whispering gallery mode resonators

Polimetilmetakrilāta (PMMA) čukstošo galeriju modu (ČGM) mikro sfēru rezonatori ir komerciāli pieejami ar tipiskajiem labuma (Q) faktoriem 10^3-10^4. Izmantojot attēlu apstrādes tehniku ar augstu izšķirtspēju (1.9µm/px), ir iespējams monitorēt absorbcijas spektru. Šajā darbā tika izstrādāta jauna veida attēlu apstrādes metode priekš ČGM mikro rezonatoriem, lai analizētu intensitātes sadalījumu atsevišķos (40-70µm) PMMA ČGM mikro rezonatoru reģionos mainot ārējos fizikālos apstākļus. Intensitātes izmaiņas var tikt izmantotas lai raksturotu augstāku kārtu modu mijiedarbību un integrētu sensoru sistēmā.Poly methyl methacrylate acrylic (PMMA) whispering gallery mode (WGM) micro sphere resonators are commercially available with typical optical quality factor of 10^3-10^4. Using image processing techniques, with (1.9µm/px) high resolution, the absorption spectrum could be monitored. In the present work a new type of image processing for WGM micro-resonators was developed, to analyze intensity distribution in separate regions for PMMA WGM micro-resonators (40-70 µm) by changing the external physical properties such as temperature and wavelength. The intensity changes can be used as a representation of higher order spacial mode groups and integrated into optical sensors