In this paper, we propose to measure the intelligence of an agent by measuring how fast its knowledge level increases after learning related tasks. In this paper, we propose a new Lifelong Machine Learning Test. An agent can pass the test if it can learn unrestricted number of tasks over time and its knowledge level can increase when new tasks are learned. In the proposed test, both an agent’s ...

The focus of this short article is on the interim evaluation of Lifelong Learning Networks (LLNs) that the Centre for Higher Education Research and Information of the Open University was commissioned to undertake by the Higher Education Funding Council for England (HEFCE) during 2007 (HEFCE, 2008). It is not the intention to go into the detail of that evaluation, but instead to do two main thin...

Lifelong machine learning (or lifelong learning) is an advanced machine learning paradigm that learns continuously, accumulates the knowledge learned in previous tasks, and uses it to help future learning. In the process, the learner becomes more and more knowledgeable and effective at learning. This learning ability is one of the hallmarks of human intelligence. However, the current dominant m...

As knowledge transfer research progresses from single transfer to lifelong learning scenarios, it becomes increasingly important to properly select the source knowledge that would best transfer to the target task. In this position paper, we describe our previous work on selective knowledge transfer and relate it to problems in lifelong learning. We also briefly discuss our ongoing work to devel...

Rapid technological change, increasing globalization and a changing world of employment with multiple roles during one’s professional life are necessitating a change from knowledge to learning societies. Full participation requires lifelong learning skills, meaning the ability to solve problems, work both independently and in a team, communicate effectively in all formats and on all levels, and...

A phenomenological study of personal experiential learning was conducted. This informed a descriptive Framework of Lifelong Learning (FoLL) which describes four facets of lifelong learning: the learner, the organisation of learning, the process for carrying out learning projects, and the breakdowns that occur during, or because of,

Lifelong machine learning methods acquire knowledge over a series of consecutive tasks, continually building upon their experience. Current lifelong learning algorithms rely upon a single learning agent that has centralized access to all data. In this paper, we extend the idea of lifelong learning from a single agent to a network of multiple agents that collectively learn a series of tasks. Eac...

Lifelong Learning is a complex environment where strategic planning, coordination and collaboration between partners are needed. Lifelong learners form a rather diverse student population with a variety of backgrounds, evolving needs and varying accessibility requirements. Making lifelong learning happen in practice requires learners becoming more aware of their own studying and thinking proces...

Educational technology is seen as key for lifelong learning, but it has yet to live up to expectation. We argue that current learning environments are typically oriented too much towards structured learning to meet the needs of the lifelong learner. Environments for lifelong learning demand a higher degree of autonomy for the learner, must be open to eclectic sources, support soft informal lear...