3,665 research outputs found
De/construction sites: Romans and the digital playground
The Roman world as attested to archaeologically and as interacted with today has its expression in a great many computational and other media. The place of visualisation within this has been paramount. This paper argues that the process of digitally constructing the Roman world and the exploration of the resultant models are useful methods for interpretation and influential factors in the creation of a popular Roman aesthetic. Furthermore, it suggests ways in which novel computational techniques enable the systematic deconstruction of such models, in turn re-purposing the many extant representations of Roman architecture and material culture
Unmasking Clever Hans Predictors and Assessing What Machines Really Learn
Current learning machines have successfully solved hard application problems,
reaching high accuracy and displaying seemingly "intelligent" behavior. Here we
apply recent techniques for explaining decisions of state-of-the-art learning
machines and analyze various tasks from computer vision and arcade games. This
showcases a spectrum of problem-solving behaviors ranging from naive and
short-sighted, to well-informed and strategic. We observe that standard
performance evaluation metrics can be oblivious to distinguishing these diverse
problem solving behaviors. Furthermore, we propose our semi-automated Spectral
Relevance Analysis that provides a practically effective way of characterizing
and validating the behavior of nonlinear learning machines. This helps to
assess whether a learned model indeed delivers reliably for the problem that it
was conceived for. Furthermore, our work intends to add a voice of caution to
the ongoing excitement about machine intelligence and pledges to evaluate and
judge some of these recent successes in a more nuanced manner.Comment: Accepted for publication in Nature Communication
Urban hydroinformatics: past, present and future
This is the author accepted manuscriptHydroinformatics, as an interdisciplinary domain that blurs boundaries between water science, data science and computer science, is constantly evolving and reinventing itself. At the heart of this evolution, lies a continuous process of critical (self) appraisal of the disciplineâs past, present and potential for further evolution, that creates a positive feedback loop between legacy, reality and aspirations. The power of this process is attested by the successful story of hydroinformatics thus far, which has arguably been able to mobilize wide ranging research and development and get the water sector more in tune with the digital revolution of the past 30 years. In this context, this paper attempts to trace the evolution of the discipline, from its computational hydraulics origins to its present focus on the complete socio-technical system, by providing at the same time, a functional framework to improve the understanding and highlight the links between different strands of the state-of-art hydroinformatic research and innovation. Building on this state-of-art landscape, the paper then attempts to provide an overview of key developments that are coming up, on the disciplineâs horizon, focusing on developments relevant to urban water management, while at the same time, highlighting important legal, ethical and technical challenges that need to be addressed to ensure that the brightest aspects of this potential future are realized. Despite obvious limitations imposed by a single paperâs ability to report on such a diverse and dynamic field, it is hoped that this work contributes to a better understanding of both the current state of hydroinformatics and to a shared vision on the most exciting prospects for the future evolution of the discipline and the water sector it serves
Principal Trade-off Analysis
How are the advantage relations between a set of agents playing a game
organized and how do they reflect the structure of the game? In this paper, we
illustrate "Principal Trade-off Analysis" (PTA), a decomposition method that
embeds games into a low-dimensional feature space. We argue that the embeddings
are more revealing than previously demonstrated by developing an analogy to
Principal Component Analysis (PCA). PTA represents an arbitrary two-player
zero-sum game as the weighted sum of pairs of orthogonal 2D feature planes. We
show that the feature planes represent unique strategic trade-offs and
truncation of the sequence provides insightful model reduction. We demonstrate
the validity of PTA on a quartet of games (Kuhn poker, RPS+2, Blotto, and
Pokemon). In Kuhn poker, PTA clearly identifies the trade-off between bluffing
and calling. In Blotto, PTA identifies game symmetries, and specifies strategic
trade-offs associated with distinct win conditions. These symmetries reveal
limitations of PTA unaddressed in previous work. For Pokemon, PTA recovers
clusters that naturally correspond to Pokemon types, correctly identifies the
designed trade-off between those types, and discovers a rock-paper-scissor
(RPS) cycle in the Pokemon generation type - all absent any specific
information except game outcomes.Comment: 17 pages, 8 figure
Exploration-Exploitation in Multi-Agent Learning: Catastrophe Theory Meets Game Theory
Exploration-exploitation is a powerful and practical tool in multi-agent
learning (MAL), however, its effects are far from understood. To make progress
in this direction, we study a smooth analogue of Q-learning. We start by
showing that our learning model has strong theoretical justification as an
optimal model for studying exploration-exploitation. Specifically, we prove
that smooth Q-learning has bounded regret in arbitrary games for a cost model
that explicitly captures the balance between game and exploration costs and
that it always converges to the set of quantal-response equilibria (QRE), the
standard solution concept for games under bounded rationality, in weighted
potential games with heterogeneous learning agents. In our main task, we then
turn to measure the effect of exploration in collective system performance. We
characterize the geometry of the QRE surface in low-dimensional MAL systems and
link our findings with catastrophe (bifurcation) theory. In particular, as the
exploration hyperparameter evolves over-time, the system undergoes phase
transitions where the number and stability of equilibria can change radically
given an infinitesimal change to the exploration parameter. Based on this, we
provide a formal theoretical treatment of how tuning the exploration parameter
can provably lead to equilibrium selection with both positive as well as
negative (and potentially unbounded) effects to system performance.Comment: Appears in the 35th AAAI Conference on Artificial Intelligenc
Tabletop Roleplaying Games as Procedural Content Generators
Tabletop roleplaying games (TTRPGs) and procedural content generators can
both be understood as systems of rules for producing content. In this paper, we
argue that TTRPG design can usefully be viewed as procedural content generator
design. We present several case studies linking key concepts from PCG research
-- including possibility spaces, expressive range analysis, and generative
pipelines -- to key concepts in TTRPG design. We then discuss the implications
of these relationships and suggest directions for future work uniting research
in TTRPGs and PCG.Comment: 9 pages, 2 figures, FDG Workshop on Procedural Content Generation
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Mapping childâcomputer interaction research through co-word analysis
This paper employs hierarchical clustering, strategic diagrams, and network analysis to construct an intellectual map of the ChildâComputer Interaction research field (CCI) and to visualize the thematic landscape of this field using co-word analysis. This approach assumes that an articleâs keywords constitute an adequate description of its content and reflect the topics that the article covers. It also assumes that the co-occurrence of two or more keywords within the same article indicates a linkage between those topics. This study quantifies the thematic landscape of the CCI field and elaborates on emerging topics as these are manifested in publications in the two primary venues of the CCI field, namely the proceedings of the annual IDC conference and the International Journal of CCI. Overall, a total of 1059 articles, and their respective 2445 unique, author-assigned keywords, are included in our analyses â all papers have been published between 2003 and 2018. The results indicate that the community has focused (i.e., high frequency keywords) in areas including Participatory Design, Tangibles, Design, Education, Coding, and Making. These areas also demonstrate a high degree of âcorenessâ (i.e., connection with different topics) and âconstraintâ (i.e., connection with otherwise isolated topics). The analysis also highlights well-structured yet peripheral topics, as well as topics that are either marginally interesting, or have the potential to become of major importance to the entire research network in the near future. Limitations of the approach and future work plans conclude the paper
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