Portugal

Paisajes distantes is a networked audio-visual performance linking human and non-human soundscapes and visuals from two cities — Bogota, Colombia and Pittsburgh, US — captured during the COVID-19 quarantine period of 2020. Conceived as a dialogue between two urban auras in isolation, the piece juxtaposes dissimilar atmospheres including sounds and imagery of ferrovial systems, water canals, urban fauna, and domestic life. These form the substrate for a live performance comprising digitally processed and computer-generated sounds including layers of granular synthesis, heavily processed guitar sounds, and additional samples. The piece will be produced remotely and in real time by the artists — who are also distant from each other, each one in one of the two cities — through a networked music performance (NMP) system. In Coimbra, the performance will be preferably experienced as an ambient intervention in an open area. Accompanying the sound will be a video screen or projection with a split image displaying visuals collected during the lockdowns in the two cities. With these elements, the piece employs digital mediations to explore different conceptions of distance — social, geographic, and affective. Captured while in the midst of an unprecedented moment of personal and collective isolation, the sonic and visual materials give structure to an improvisational, networked digital music performance. Paisajes distantes thus reflects on the possibilities of new encounters, new forms of presence, and new modes of creative engagement shaped by the necessity of isolation and enabled by digital networks and computational processes.

ICCC&#39;20

Paisajes distantes

social distance

altiplano

networked music performance

co-presence

Brought to you by **National Defense Industrial Association ([NDIA](https://www.google.com/url?q=https%3A%2F%2Fwww.ndia-sd.org%2F&sa=D&sntz=1&usg=AFQjCNHj_BQx1K4KVKKp1NTIsAltZOG9Vg))** and hosted by the **Battlespace Exploitation of Mixed Reality ([BEMR](https://cdn.dvidshub.net/media/video/2101/DOD_108139354/DOD_108139354-1024x576-1769k.mp4)) Lab**, at **Naval Information Warfare Center Pacific ([NIWC PAC](https://www.google.com/url?q=https%3A%2F%2Fwww.public.navy.mil%2Fnavwar%2FNIWC-Pacific%2FPages%2Fdefault.aspx&sa=D&sntz=1&usg=AFQjCNFNS160IEsocfaBrnCNB3u7NqLHPw))**, and welcoming academia, government/DOD, and industry leaders who support Industrial Augmented Reality/Virtual Reality by using the following technologies:   


* Augmented Reality (AR) / Virtual Reality (VR)

* 2D/3D displays

* mobile displays

* wearables

* any other "immersive" technology

### In all fields that touch:

* 3D modeling

* Manufacturing 

* Installations 

* Maintenance and Repairs

* Construction

* Logistics

* Additive manufacturing

* Training

The technical exchange is a two day event held online this year due to COVID-19. It will feature two days of oral presentations, demonstrations, and posters from leaders in AR/VR and other display technologies, including government briefings on active projects within the DOD. The technical exchange is unclassified and we welcome participation from the Navy, DoD as well as from industry and academia. 

The goals of TEAR 3M are:

*  To spread awareness of current immersive technology research relevant to Navy/DOD applications

*  To connect AR researchers with experts in DOD to learn about needs and requirements

*  To build and strengthen collaborations within the DOD research community

![](https://assets.underline.io/uploads/markdown_image/1/image/0c13ac0ffa096b2353573964d8b89789.png)

TEAR 3M General Chairs:

Heidi Buck,  Director @ BEMR Lab, Naval Information Warfare Center, Pacific

Lauren Burnette, BEMR Lab, Naval Information Warfare Center, Pacific


For more information, contact Lauren and Heidi at:  tear3m@spawar.navy.mil

Questions regarding sponsorship/registration contact:  ndiasd@sandiegositepros.com

Conference host POC is Tammy Sanchez (NDIA):  tamsanch@cisco.com

TEAR 3M 2021

technical paper

Computational creativity is the art, science, philosophy and engineering of computational systems which, by taking on particular responsibilities, exhibit behaviours that unbiased observers would deem to be creative. As a field of research, this area is thriving, with progress in formalising what it means for software to be creative, along with many exciting and valuable applications of creative software in the sciences, the arts, literature, gaming and elsewhere.

The ICCC conference series organized by the Association for Computational Creativity since 2010 is the only scientific conference that focuses on computational creativity alone and also covers all aspects of it.


ICCC'20

The ICCC conference series organized by the Association for Computational Creativity since 2010 is the only scientific conference that focuses on computational creativity alone and also covers all aspects of it.
Computational creativity is the art, science, philosophy and engineering of computational systems which, by taking on particular responsibilities, exhibit behaviors that unbiased observers would deem to be creative. As a field of research, this area is thriving, with progress in formalizing what it means for software to be creative, along with many exciting and valuable applications of creative software in the sciences, the arts, literature, gaming and elsewhere.



We  argue  that  frameworks  employed  in  architecting self-adaptive systems allow the system to exhibit creative  behaviour,  and  that  many  of  the  existing  self-adaptive systems operating in domains which are typically not associated with creativity are inherently creative.  However, even the current state-of-the-art solutions do not fully exploit stronger forms of creative behaviour, which are required in complex environments, where the system constantly encounters fundamentally novel situations.  To this end, software development necessitates a paradigm shift parallel to moving from procedural design methodology toward self-aware systems where the system adapts to its context at run time.

On the Inherent Creativity of Self-Adaptive Systems

"With an increase in the number of mobile apps making their way to users, there is a growing need for tools to support the app design process. While many tools focus
on increasing the pace of development, few attempt to aide the designer in generating more creative solutions. In this work, we take creativity as the combination of novelty and utility. Particularly during development of user interfaces, assessment of utility (primarily usability) is iterative, rigorous, and time-consuming. The objective of the proposed work is to explore and evaluate the use of machine learning to predict usability measures for mobile app interfaces as a means to automate usability evaluations. Specifically, a convolutional neural network (CNN) is used to accurately (nearly 90%) predict three usability measures: regularity, complexity, and touchability. This tool automates the assessment of utility in app design, freeing up the designer to seek designs that are novel and thus creative."

Towards Enhanced Creativity in Interface Design through Automated Usability Evaluation

This presentation outlines how a system based on a society of many thousands of micro-agents could produce a narrative which describes a simple situation. The distributed nature of the system should allow for a more diverse range of possible pathways to be taken towards a solution as well as an interweaving of the processes of production and comprehension (or engagement and reflection). This should result in greater cognitive plausibility than models made up out of a small number of large modules.

Creative Language Generation in a Society of Engagement and Reflection

Creative problem solving (CPS) is a skill that can greatly improve resourcefulness and adaptability of existing artificial intelligence (AI) systems. In this paper, we discuss how CPS leverages theoretical aspects from Computational Creativity (CC) and planning in AI. We present a definition of CPS, and discuss how CPS is achieved using aspects of CC and problem solving in AI.

From Computational Creativity to Creative Problem Solving Agents

"Recently, models in Computational Cognitive Neuroscience (CCN) have gained a renewed interest because they could help analyze current limitations in Artificial
Intelligence (AI) and propose operational ways to address them. These limitations are related to difficulties in giving a semantic grounding to manipulated concepts,
in coping with high dimensionality and in managing uncertainty. In this paper, we describe the main principles and mechanisms of these models and explain that they can be directly transferred to Computational Creativity (CC), to propose operational mechanisms but also a better understanding of what creativity is."

Creativity explained by Computational Cognitive Neuroscience

This work describes the story of the Mexican International Colloquium on Computational Creativity, which has been carried out for 14 years. I describe the activities around this academic event and present a list of all invited speakers. I finish with some thoughts about the experience of organizing this Colloquium.

Mexican International Colloquium on Computational Creativity

"Sound and movement are closely coupled, particularly in dance.
Certain audio features have been found to affect the way we move to music.
Is this relationship between sound and movement something which can be modelled using machine learning? 
This work presents initial experiments wherein
high-level audio features calculated from a set of music pieces are included in a movement generation model trained on motion capture recordings of improvised dance.  Our results indicate that the model learns to generate realistic dance movements which vary depending on the audio features."

Towards Movement Generation with Audio Features

Creative design is often accomplished through teams, and the specific composition of those teams can limit or enhance the sum creativity. However, it is not known how team composition is related to a team’s ability to achieve good solutions over various problems (i.e., robustness). Here, we build that relationship between composition and robustness through a series of agent-based simulations. The factor that we specifically investigate is cognitive style, which describes the manner in which individuals solve problems and present solutions in social interactions based on cognitive processes. Under Kirton’s Adaption Innovation (KAI) Theory, cognitive style is related to creativity. Specifically, an individual’s KAI score, the defining measure of cognitive style, describes the degree to which they prefer high-utility solutions, or high-novelty solutions – the two necessary conditions for creativity. In many cases the long-term success of a team is closely tied to their ability to perform consistently well across multiple design problems, termed robustness. Leveraging computational agents, we use adaption-innovation theory as the primary factor to examine robustness among homogenous and heterogeneous agents. Different approaches to composing teams with homogenous and heterogeneous cognitive styles did not substantially impact robustness. However, the average robustness of the teams improved as team size increased.

Utilizing Agent-Based Modeling to Quantify Robustness in Design Teams With Respect to Cognitive Style

"Creativity is the generation of an artifact that is judged to be novel and high-quality. Several computational creativity systems with diverse algorithmic foundations are
now meeting standards of novelty and quality, as judged by experts in creative fields. The existence of these myriad design approaches suggest a natural question analogous to the one addressed in information theory: Are there fundamental limits to creativity? Here, we first review a recent mathematical formalism that captures key aspects of combinatorial creativity and yields fundamental tradeoffs between novelty and quality. The fundamental limit resembles Shannon’s capacity-cost function. Then we extend the theory to capture intentionality in creativity, treating it as a communication problem, where a creative artifact must not only be novel and high-quality, but also reliably convey a message of given information rate. The resulting fundamental limit resembles the information bottleneck optimization
in machine learning."

Limits Theorems for Creativity with Intentionality

Computers can help us to trigger our intuition about how to solve a problem. But how does a computer take into account what a user wants and update these triggers? User preferences are hard to model as they are by nature vague, depend on the user's background and are not always deterministic, changing depending on the context and process under which they were established. We pose that the process of preference discovery should be the object of interest in computer aided design or ideation. The process should be transparent, informative, interactive and intuitive. We formulate HyperPref, a cyclic co-creative process between human and computer, which triggers the user's intuition about what is possible and is updated according to what the user wants based on their decisions. We combine quality diversity algorithms, a divergent optimization method that can produce many, diverse solutions, with variational autoencoders to both model that diversity as well as the user's preferences, discovering the preference hypervolume within large search spaces.

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