Supportive and Antagonistic Behaviour in Distributed Computational Creativity via Coupled Empowerment Maximisation

There has been a strong tendency in distributed computational creativity systems to embrace embodied and situated agents for their flexible and adaptive behaviour. Intrinsically motivated agents are particularly successful in this respect, because they do not rely on externally specified goals, and can thus react flexibly to changes in open-ended environments. While supportive and antagonistic behaviour is omnipresent when people interact in creative tasks, existing implementations cannot establish such behaviour without constraining their agents’ flexibility by means of explicitly specified interaction rules. More open approaches in contrast cannot guarantee that support or antagonistic behaviour ever comes about. We define the information-theoretic principle of coupled empowerment maximisation as an intrinsically motivated frame for supportive and antagonistic behaviour within which agents can interact with maximum flexibility. We provide an intuition and a formalisation for an arbitrary number of agents. We then draw on several case-studies of co-creative and social creativity systems to make detailed predictions of the potential effect the underlying empowerment maximisation principle might have on the behaviour of creative agents

Supportive and Antagonistic Behaviour in Distributed Computational Creativity via Coupled Empowerment Maximisation

Abstract There has been a strong tendency in distributed computational creativity systems to embrace embodied and situated agents for their flexible and adaptive behaviour. Intrinsically motivated agents are particularly successful in this respect, because they do not rely on externally specified goals, and can thus react flexibly to changes in open-ended environments. While supportive and antagonistic behaviour is omnipresent when people interact in creative tasks, existing implementations cannot establish such behaviour without constraining their agents' flexibility by means of explicitly specified interaction rules. More open approaches in contrast cannot guarantee that support or antagonistic behaviour ever comes about. We define the information-theoretic principle of coupled empowerment maximisation as an intrinsically motivated frame for supportive and antagonistic behaviour within which agents can interact with maximum flexibility. We provide an intuition and a formalisation for an arbitrary number of agents. We then draw on several case-studies of co-creative and social creativity systems to make detailed predictions of the potential effect the underlying empowerment maximisation principle might have on the behaviour of creative agents

Intrinsic Motivation in Computational Creativity Applied to Videogames

PhD thesisComputational creativity (CC) seeks to endow artificial systems with creativity. Although human creativity is known to be substantially driven by intrinsic motivation (IM), most CC systems are extrinsically motivated. This restricts their actual and perceived creativity and autonomy, and consequently their benefit to people. In this thesis, we demonstrate, via theoretical arguments and through applications in videogame AI, that computational intrinsic reward and models of IM can advance core CC goals. We introduce a definition of IM to contextualise related work. Via two systematic reviews, we develop typologies of the benefits and applications of intrinsic reward and IM models in CC and game AI. Our reviews highlight that related work is limited to few reward types and motivations, and we thus investigate the usage of empowerment, a little studied, information-theoretic intrinsic reward, in two novel models applied to game AI. We define coupled empowerment maximisation (CEM), a social IM model, to enable general co-creative agents that support or challenge their partner through emergent behaviours. Via two qualitative, observational vignette studies on a custom-made videogame, we explore CEM’s ability to drive general and believable companion and adversary non-player characters which respond creatively to changes in their abilities and the game world. We moreover propose to leverage intrinsic reward to estimate people’s experience of interactive artefacts in an autonomous fashion. We instantiate this proposal in empowerment-based player experience prediction (EBPXP) and apply it to videogame procedural content generation. By analysing think-aloud data from an experiential vignette study on a dedicated game, we identify several experiences that EBPXP could predict. Our typologies serve as inspiration and reference for CC and game AI researchers to harness the benefits of IM in their work. Our new models can increase the generality, autonomy and creativity of next-generation videogame AI, and of CC systems in other domains

Role-Based Perceptions of Computer Participants in Human-Computer Co-Creativity

The purpose of this ongoing research is to better un- derstand the potential contributions that computers can play in sit- uations where people interact with computers towards creative pur- suits and goals. Past research has provided sets of definitions of dif- ferent roles that a computer plays in human-computer creative col- laboration. Thus far, we look into the advantages and limitations of having such roles. In particular, this paper contributes an analysis and categorisation of the coverage of existing role classifications for computational participants in co-creativity. This analysis is comple- mented by a comparative review of the use of roles to understand and structure creative collaboration between people only (i.e. without any computational participants involved). Our wider project investigates whether these defined sets of roles are a. adequate and b. helpful for understanding the perception of computational contributions in co-creativity, with a study planned to investigate the roles of current systems in practice. This project considers both co-creative computer systems that currently exist, and systems that could potentially exist in the future. Our goal is to reach a point where the perception of what is possible in human-computer co-creative collaboration is en- abled and boosted (but not constrained) by a definitive set of roles

New And Surprising Ways to Be Mean: Adversarial NPCs with Coupled Empowerment Minimisation

Creating Non-Player Characters (NPCs) that can react robustly to unforeseen player behaviour or novel game content is difficult and time-consuming. This hinders the design of believable characters, and the inclusion of NPCs in games that rely heavily on procedural content generation. We have previously addressed this challenge by means of empowerment, a model of intrinsic motivation, and demonstrated how a coupled empowerment maximisation (CEM) policy can yield generic, companion-like behaviour. In this paper, we extend the CEM framework with a minimisation policy to give rise to adversarial behaviour. We conduct a qualitative, exploratory study in a dungeon-crawler game, demonstrating that CEM can exploit the affordances of different content facets in adaptive adversarial behaviour without modifications to the policy. Changes to the level design, underlying mechanics and our character's actions do not threaten our NPC's robustness, but yield new and surprising ways to be mean

Expanding the Active Inference Landscape: More Intrinsic Motivations in the Perception-Action Loop

Active inference is an ambitious theory that treats perception, inference, and action selection of autonomous agents under the heading of a single principle. It suggests biologically plausible explanations for many cognitive phenomena, including consciousness. In active inference, action selection is driven by an objective function that evaluates possible future actions with respect to current, inferred beliefs about the world. Active inference at its core is independent from extrinsic rewards, resulting in a high level of robustness across e.g., different environments or agent morphologies. In the literature, paradigms that share this independence have been summarized under the notion of intrinsic motivations. In general and in contrast to active inference, these models of motivation come without a commitment to particular inference and action selection mechanisms. In this article, we study if the inference and action selection machinery of active inference can also be used by alternatives to the originally included intrinsic motivation. The perception-action loop explicitly relates inference and action selection to the environment and agent memory, and is consequently used as foundation for our analysis. We reconstruct the active inference approach, locate the original formulation within, and show how alternative intrinsic motivations can be used while keeping many of the original features intact. Furthermore, we illustrate the connection to universal reinforcement learning by means of our formalism. Active inference research may profit from comparisons of the dynamics induced by alternative intrinsic motivations. Research on intrinsic motivations may profit from an additional way to implement intrinsically motivated agents that also share the biological plausibility of active inference

Nurturing emergent agency: networks and dynamics of complex social change processes in Raipur, India

This thesis takes up the question, how can agency for people living in informal settlements be strengthened? To address this question, I carried out systemic action research with two NGO partners and residents from seven informal settlements in Raipur, India. This involved organizing ‘slum improvement committees’ (SICs) in each of the seven settlements and carrying out joint actions in support of housing rights and implementation of the Rajiv Awas Yojana (RAY) housing policy. The data on which my analysis is based includes over one hundred conversations between myself and the project participants (both from the settlements as well as the partner NGOs), records of two public events, a social network survey of 46 people living in the participating settlements, a separate set of 9 participatory social network maps (NetMaps), and over two hundred pages of my own field notes based on my observations and participation in the research activities. My thesis makes an original contribution to the study of community agency by analysing it through the lens of complex systems theories and utilising the tools of social network analysis. My thesis also makes an original contribution to research methodology by making the technical analysis participatory, accessible, and useful for the participants. This allowed me to combine analysis of relational structures (social networks) with relational dynamics to show how significant social change happened over the course of the project. My thesis suggests that agency can be strengthened through an organizing practice that brings NGOs, academic researchers, and residents of informal settlements together to build relational power, take collective action, and create social change

Drivers of flow and commitment among service workers : an empirical exploration of Goffman’s institutions in the UK Branded Restaurant Industry

This thesis explores the theory of Goffman’s institutions and applies his concept to the UK Branded Restaurant Industry. Restaurants in the UK are a large part of the tourism hospitality industry, representing around 50% of the business activity in these fields, of which we see dominance from a number of branded operators. Goffman’s institutions, flow, commitment, motivation, spirituality, and deviant behaviour are combined to create a theoretical underpinning for an empirical analysis of staff working in the field. The research focuses on the drivers of flow and commitment of staff. The study successfully applies Goffman’s theory of institutions to the UK Branded Restaurant Industry, by finding similarity in the concepts which are central to those of a traditional asylum, as discussed in Goffman’s early works, and contributing additional aspects to his original theories. The study is the first large scale empirical analysis to examine the nature of flow, commitment, motivation, spirituality, and deviant behaviour, in the context of UK Branded Restaurants. Within the study, the findings show that there is gender parity in this section of the tourism and hospitality industry, which deviates from previous literature. It also identifies key groups of employees who demonstrate higher levels of commitment through intrinsic values and belief systems. The findings are particularly important to managers as they point what is important when identifying new staff members