Introduction to special Issue: future priorities in European media and communication research

(Excerto) The European Journal of Communication seeks to present the best in current research in the broad field of media and communication research. Irregularly, we seek to take stock by inviting a small group of leading scholars to present their work at a symposium on a common theme, which then forms the basis for a Special Issue of the Journal. In 2014, the European Science Foundation (ESF) published one of their ‘Forward Looks’ entitled Media in Europe: New Questions for Research and Policy. We subsequently invited several of the Forward Look’s authors to meet and discuss their work with us at a symposium hosted by the European University Cyprus, and the discussion and revised papers that resulted are published here.

Introduction [to "Citizen voices: performing public participation in science and environment communication"]

"ECREA series, ISSN 1742-9420"

Off-line simulation inspires insight: a neurodynamics approach to efficient robot task learning

There is currently an increasing demand for robots able to acquire the sequential organization of tasks from social learning interactions with ordinary people. Interactive learning-by-demonstration and communication is a promising research topic in current robotics research. However, the efficient acquisition of generalized task representations that allow the robot to adapt to different users and contexts is a major challenge. In this paper, we present a dynamic neural field (DNF) model that is inspired by the hypothesis that the nervous system uses the off-line re-activation of initial memory traces to incrementally incorporate new information into structured knowledge. To achieve this, the model combines fast activation-based learning to robustly represent sequential information from single task demonstrations with slower, weight-based learning during internal simulations to establish longer-term associations between neural populations representing individual subtasks. The efficiency of the learning process is tested in an assembly paradigm in which the humanoid robot ARoS learns to construct a toy vehicle from its parts. User demonstrations with different serial orders together with the correction of initial prediction errors allow the robot to acquire generalized task knowledge about possible serial orders and the longer term dependencies between subgoals in very few social learning interactions. This success is shown in a joint action scenario in which ARoS uses the newly acquired assembly plan to construct the toy together with a human partner.

On trust, knowledge, sharing and innovation

Organisations continuously innovate, create, and are competitive if they improve their performance through continuous intellectual capital development, a key resource for value creation and organisational performance driver. Apart from sustaining competitive advantage, intellectual capital is increasingly important due to its ability to increase shareholder value, especially in public organisations. Employee learning, talent development, and knowledge creation allow the organisation to generate innovative ideas due to the quickness of knowledge obsolescence. The organisation's dynamic capabilities create and re-ignite organisational competencies for business sustainability being co-ordinated by well-structured organisational strategic routines ensuring continuous value creation streams into the business. This chapter focuses on the relationship between notions of knowledge sharing and trust in organisations. Lack of trust can impact negatively organisational knowledge sharing, dependent on trust, openness, and communication. The research sample included graduates and postgraduate students from two universities in Portugal. The findings revealed different perceptions according to the age group.