Natural Language Does Not Emerge 'Naturally' in Multi-Agent Dialog

A number of recent works have proposed techniques for end-to-end learning of communication protocols among cooperative multi-agent populations, and have simultaneously found the emergence of grounded human-interpretable language in the protocols developed by the agents, all learned without any human supervision! In this paper, using a Task and Tell reference game between two agents as a testbed, we present a sequence of 'negative' results culminating in a 'positive' one -- showing that while most agent-invented languages are effective (i.e. achieve near-perfect task rewards), they are decidedly not interpretable or compositional. In essence, we find that natural language does not emerge 'naturally', despite the semblance of ease of natural-language-emergence that one may gather from recent literature. We discuss how it is possible to coax the invented languages to become more and more human-like and compositional by increasing restrictions on how two agents may communicate.Comment: 9 pages, 7 figures, 2 tables, accepted at EMNLP 2017 as short pape

Using Visualization to Support Data Mining of Large Existing Databases

In this paper. we present ideas how visualization technology can be used to improve the difficult process of querying very large databases. With our VisDB system, we try to provide visual support not only for the query specification process. but also for evaluating query results and. thereafter, refining the query accordingly. The main idea of our system is to represent as many data items as possible by the pixels of the display device. By arranging and coloring the pixels according to the relevance for the query, the user gets a visual impression of the resulting data set and of its relevance for the query. Using an interactive query interface, the user may change the query dynamically and receives immediate feedback by the visual representation of the resulting data set. By using multiple windows for different parts of the query, the user gets visual feedback for each part of the query and, therefore, may easier understand the overall result. To support complex queries, we introduce the notion of approximate joins which allow the user to find data items that only approximately fulfill join conditions. We also present ideas how our technique may be extended to support the interoperation of heterogeneous databases. Finally, we discuss the performance problems that are caused by interfacing to existing database systems and present ideas to solve these problems by using data structures supporting a multidimensional search of the database

Generating collaborative systems for digital libraries: A model-driven approach

This is an open access article shared under a Creative Commons Attribution 3.0 Licence (http://creativecommons.org/licenses/by/3.0/). Copyright @ 2010 The Authors.The design and development of a digital library involves different stakeholders, such as: information architects, librarians, and domain experts, who need to agree on a common language to describe, discuss, and negotiate the services the library has to offer. To this end, high-level, language-neutral models have to be devised. Metamodeling techniques favor the definition of domainspecific visual languages through which stakeholders can share their views and directly manipulate representations of the domain entities. This paper describes CRADLE (Cooperative-Relational Approach to Digital Library Environments), a metamodel-based framework and visual language for the definition of notions and services related to the development of digital libraries. A collection of tools allows the automatic generation of several services, defined with the CRADLE visual language, and of the graphical user interfaces providing access to them for the final user. The effectiveness of the approach is illustrated by presenting digital libraries generated with CRADLE, while the CRADLE environment has been evaluated by using the cognitive dimensions framework

Using Video Games to Develop Graduate Attributes: a Pilot Study

It may be argued that most higher education courses are not explicitly designed to teach or develop desirable soft skills such as critical thinking, communication, resourcefulness or adaptability. While such skills – often referred to as ‘graduate attributes’ – are assumed to be developed as a by-product of a university education, there is little empirical evidence to support this assumption. Furthermore, traditional didactic teaching methods do not typically require students to exhibit such skills, while prevalent assessment methods such as examinations are ill-suited to measure them. Many commercial video games, on the other hand, require players to exercise a range of very similar skills and competencies in order to progress. The pilot project described here sought to explore the use of video games to develop graduate attributes and to identify suitable instruments for measuring such elusive conceptions. A small group of undergraduate students were recruited and asked to play selected video games for two hours per week over an eight week period. A range of psychometric tests were administered at the beginning and the end of the experiment period in order to gather empirical data relating to the participants’ graduate attributes. Mean differences in the pre- and post-intervention scores associated with each measure were obtained and 95% confidence intervals calculated to provide an indication of whether results obtained might be indicative of a wider population. Participants were also asked to discuss their experience as a group following each session and to blog about it if they were so inclined. Despite the small scale of the pilot, the results were sufficiently encouraging to warrant a larger study, which is now underway. The challenges involved in obtaining empirical data on the effectiveness of a game-based intervention such as this are addressed and implications for the subsequent study are discussed