A Formal Architecture of Shared Mental Models for Computational Improvisational Agents

This paper proposes a formal approach of constructing shared mental models between computational improvisational agents (improv agents) and human interactors based on our socio-cognitive studies of human improvisers. Creating shared mental models helps improv agents co-create stories with each other and interactors in real-time interactive narrative experiences. The approach described here allows flexible modeling of non-Boolean (i.e. fuzzy) knowledge about scene and background concepts through the use of fuzzy rules and confidence factors in order to allow reasoning under uncertainty. It also allows improv agents to infer new knowledge about a scene from existing knowledge, recognize when new knowledge may be divergent from the other actor’s mental model, and attempt to resolve this divergence to reach cognitive consensus despite the absence of explicit goals in the story environment

Pharaoh: Conceptual Blending of Cognitive Scripts for Computationally Creative Agents

Improvisational acting is a creative group performance where actors co-construct stories on stage in real-time based on actors’ perceptions of the environment. The Digital Improv Project has been engaged in a multi-year study of the cognitive processes involved in improvisational acting. This better understanding of human cognition and creativity has led to formal computational models of some aspects of our findings. In this work, we consider enriching AI improv agents with the ability to improvise new nontraditional scenes based on existing social cognitive scripts. This paper shows how the use of Pharaoh -a context based structural retrieval algorithm for cognitive scripts- and simple blending rules can help digital improv agents to create new interesting scenes. The paper also provides an illustrative example at the end

Reaching Cognitive Consensus with Improvisational Agents

A common approach to interactive narrative involves imbuing the computer with all of the potential story pre- authored story experiences (e.g. as beats, plot points, planning operators, etc.). This has resulted in an accepted paradigm where stories are not created by or with the user; rather, the user is given piecemeal access to the story from the gatekeeper of story knowledge: the computer (e.g. as an AI drama manager). This article describes a formal process that provides for the equal co-creation of story-rich experiences, where neither the user nor computer is in a privileged position in an interactive narrative. It describes a new formal approach that acts as a first step for the realtime co-creation of narrative in games that rely on the negotiated shared mental model between a human actor and an AI improv agent

An Enactivist Model of Improvisational Dance

An Enactivist Model of Improvisational Danc

A Subsumption Agent for Collaborative Free Improvisation

This paper discusses the design and evaluation of an artificial agent for collaborative musical free improvisation. The agent provides a means to investigate the underpinnings of improvisational interaction. In connection with this general goal, the system is also used here to explore the implementation of a collaborative musical agent using a specific robotics architecture, Subsumption. The architecture of the system is explained, and its evaluation in an empirical study with expert improvisors is discussed. A follow-up study using a second iteration of the system is also presented. The system design and connected studies bring together Subsumption robotics, ecological psychology, and musical improvisation, and contribute to an empirical grounding of an ecological theory of improvisation

Investigating the cognitive foundations of collaborative musical free improvisation: Experimental case studies using a novel application of the subsumption architecture

This thesis investigates the cognitive foundations of collaborative musical free improvisation. To explore the cognitive underpinnings of the collaborative process, a series of experimental case studies was undertaken in which expert improvisors performed with an artificial agent. The research connects ecological musicology and subsumption robotics, and builds upon insights from empirical psychology pertaining to the attribution of intentionality. A distinguishing characteristic of free improvisation is that no over-arching framework of formal musical conventions defines it, and it cannot be positively identified by sound alone, which poses difficulties for traditional musicology. Current musicological research has begun to focus on the social dimension of music, including improvisation. Ecological psychology, which focuses on the relation of cognition to agent–environment dynamics using the notion of affordances, has been shown to be a promising approach to understanding musical improvisation. This ecological approach to musicology makes it possible to address the subjective and social aspects of improvised music, as opposed to the common treatment of music as objective and neutral. The subjective dimension of musical listening has been highlighted in music cognition studies of cue abstraction, whereby listeners perceive emergent structures while listening to certain forms of music when no structures are identified in advance. These considerations informed the design of the artificial agent, Odessa, used for this study. In contrast to traditional artificial intelligence (AI), which tends to view the world as objective and neutral, behaviour-based robotics historically developed around ideas similar to those of ecological psychology, focused on agent–environment dynamics and the ability to deal with potentially rapidly changing environments. Behaviour-based systems that are designed using the subsumption architecture are robust and flexible in virtue of their modular, decentralised design comprised of simple interactions between simple mechanisms. The competence of such agents is demonstrated on the basis of their interaction with the environment and ability to cope with unknown and dynamic conditions, which suggests the concept of improvisation. This thesis documents a parsimonious subsumption design for an agent that performs musical free improvisation with human co-performers, as well as the experimental studies conducted with this agent. The empirical component examines the human experience of collaborating with the agent and, more generally, the cognitive psychology of collaborative improvisation. The design was ultimately successful, and yielded insights about cognition in collaborative improvisation, in particular, concerning the central relationship between perceived intentionality and affordances. As a novel application of the subsumption architecture, this research contributes to AI/robotics and to research on interactive improvisation systems. It also contributes to music psychology and cognition, as well as improvisation studies, through its empirical grounding of an ecological model of musical interaction

Choreographic and Somatic Approaches for the Development of Expressive Robotic Systems

As robotic systems are moved out of factory work cells into human-facing environments questions of choreography become central to their design, placement, and application. With a human viewer or counterpart present, a system will automatically be interpreted within context, style of movement, and form factor by human beings as animate elements of their environment. The interpretation by this human counterpart is critical to the success of the system's integration: knobs on the system need to make sense to a human counterpart; an artificial agent should have a way of notifying a human counterpart of a change in system state, possibly through motion profiles; and the motion of a human counterpart may have important contextual clues for task completion. Thus, professional choreographers, dance practitioners, and movement analysts are critical to research in robotics. They have design methods for movement that align with human audience perception, can identify simplified features of movement for human-robot interaction goals, and have detailed knowledge of the capacity of human movement. This article provides approaches employed by one research lab, specific impacts on technical and artistic projects within, and principles that may guide future such work. The background section reports on choreography, somatic perspectives, improvisation, the Laban/Bartenieff Movement System, and robotics. From this context methods including embodied exercises, writing prompts, and community building activities have been developed to facilitate interdisciplinary research. The results of this work is presented as an overview of a smattering of projects in areas like high-level motion planning, software development for rapid prototyping of movement, artistic output, and user studies that help understand how people interpret movement. Finally, guiding principles for other groups to adopt are posited.Comment: Under review at MDPI Arts Special Issue "The Machine as Artist (for the 21st Century)" http://www.mdpi.com/journal/arts/special_issues/Machine_Artis

E-Drama: Facilitating Online Role-play using an AI Actor and Emotionally Expressive Characters.

This paper describes a multi-user role-playing environment, e-drama, which enables groups of people to converse online, in scenario driven virtual environments. The starting point of this research – edrama – is a 2D graphical environment in which users are represented by static cartoon figures. An application has been developed to enable integration of the existing edrama tool with several new components to support avatars with emotionally expressive behaviours, rendered in a 3D environment. The functionality includes the extraction of affect from open-ended improvisational text. The results of the affective analysis are then used to: (a) control an automated improvisational AI actor – EMMA (emotion, metaphor and affect) that operates a bit-part character in the improvisation; (b) drive the animations of avatars using the Demeanour framework in the user interface so that they react bodily in ways that are consistent with the affect that they are expressing. Finally, we describe user trials that demonstrate that the changes made improve the quality of social interaction and users’ sense of presence. Moreover, our system has the potential to evolve normal classroom education for young people with or without learning disabilities by providing 24/7 efficient personalised social skill, language and career training via role-play and offering automatic monitoring

The ixiQuarks: merging code and GUI in one creative space

This paper reports on ixiQuarks; an environment of instruments and effects that is built on top of the audio programming language SuperCollider. The rationale of these instruments is to explore alternative ways of designing musical interaction in screen-based software, and investigate how semiotics in interface design affects the musical output. The ixiQuarks are part of external libraries available to SuperCollider through the Quarks system. They are software instruments based on a non- realist design ideology that rejects the simulation of acoustic instruments or music hardware and focuses on experimentation at the level of musical interaction. In this environment we try to merge the graphical with the textual in the same instruments, allowing the user to reprogram and change parts of them in runtime. After a short introduction to SuperCollider and the Quark system, we will describe the ixiQuarks and the philosophical basis of their design. We conclude by looking at how they can be seen as epistemic tools that influence the musician in a complex hermeneutic circle of interpretation and signification

Computational Systems for Music Improvisation

Computational music systems that afford improvised creative interaction in real time are often designed for a specific improviser and performance style. As such the field is diverse, fragmented and lacks a coherent framework. Through analysis of examples in the field we identify key areas of concern in the design of new systems, which we use as categories in the construction of a taxonomy. From our broad overview of the field we select significant examples to analyse in greater depth. This analysis serves to derive principles that may aid designers scaffold their work on existing innovation. We explore successful evaluation techniques from other fields and describe how they may be applied to iterative design processes for improvisational systems. We hope that by developing a more coherent design and evaluation process, we can support the next generation of improvisational music systems