A Framework for Long-Term Learning Systems
نویسنده
چکیده
Increasing amounts of data have made the use of machine learning techniques much more widespread. A lot of research in machine learning has been dedicated to the design and application of effective and efficient algorithms to explain or predict facts. The development of intelligent machines that can learn over extended periods of time, and that improve their abilities as they execute more tasks, is still a pending contribution from computer science to the world. This weakness has been recognised for some decades, and an interest to solve it seems to be increasing, as demonstrated by recent leading work and broader discussions at main events in the field [Chen et al., 2016]. Our research is intended to help fill that gap.
منابع مشابه
Dynamic Harmonic Analysis of Long Term over Voltages Based on Time Varying Fourier series in Extended Harmonic Domain
Harmonics have become an important issue in modern power systems. The widespread penetration of non-linear loads to emerging power systems has turned power quality analysis into an important operation issue under both steady state and transient conditions. This paper employs an Extended Harmonic Domain (EHD) based framework for dynamic analysis of long term analysis over voltages during the tra...
متن کاملPresenting a Framework for Supporting Life-long Learning in Iranian public libraries and Its validation
Purpose: Since nowadays public libraries are considered lifelong learning centers, these centers must have the required standards and conditions to support lifelong learning in order that they could help society members to achieve their personal and professional learning more effectively. Accordingly, it is necessary to develop and provide a mechanism to support lifelong learning in public libr...
متن کاملThe Effect of Mnemonic Key Word Method on Vocabulary Learning and Long Term Retention
Most of the studies on the key word method of second/foreign language vocabulary learning have been based on the evidence from laboratory experiments and have primarily involved the use of English key words to learn the vocabularies of other languages. Furthermore, comparatively quite limited number of such studies is done in authentic classroom contexts. The present study inquired into the eff...
متن کاملThe Evolution of Long-term Care Programs; Comment on “Financing Long-term Care: Lessons From Japan”
The need for long-term care (LTC) represents a “new social risk,” one that overlaps with and complements systems of care that pre-date such programs, complicating LTC program design. This commentary expands on Ikegami’s discussion of how these structural factors must be accommodated, as well as historical and cultural factors that influence public expectations of such a...
متن کاملFinancing Long-term Care: Some Ideas From Switzerland; Comment on “Financing Long-term Care: Lessons From Japan”
Ikegami reviews the implementation of mandatory long-term care insurance systems in Germany and Japan, which are organized as pay-as-you-go systems. I propose to go one step further and implement a multi-pillar, mandatory and voluntary long-term care financing system, which combines pay-as-you-go with capital-funded elements. The proposal is based on the observation tha...
متن کاملUtilizing Generalized Learning Automata for Finding Optimal Policies in MMDPs
Multi agent Markov decision processes (MMDPs), as the generalization of Markov decision processes to the multi agent case, have long been used for modeling multi agent system and are used as a suitable framework for Multi agent Reinforcement Learning. In this paper, a generalized learning automata based algorithm for finding optimal policies in MMDP is proposed. In the proposed algorithm, MMDP ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2017