Luovat järjestelmät, toimijat sekä yhteisöt : Teoreettisia analyysimenetelmiä ja empiirisiä yhteistyötutkimuksia

Creativity is a multi-faceted phenomenon that can be observed in diverse individuals and contexts, both natural and artificial. This thesis studies computational creativity, i.e. creativity in machines, which can be broadly categorised as a subfield of artificial intelligence. In particular, the thesis deals with three important perspectives on computational creativity: (1) identifying properties of creative individuals, (2) studying processes that lead to creative outcomes, and (3) observing and analysing social aspects of creativity, e.g. collaboration which may allow the individuals to create something together which they could not do alone. One of the key interests in computational creativity is how computational entities may exhibit creativity in their own right, implying that the creative entities and their compositions, roles, processes and interactions are potentially different from those encountered in nature. This calls for theoretical analysis methods specifically tailored for artificial creative entities, and carefully controlled empirical experiments and simulations with them. We study both of these aspects. The analysis methods allow us to scrutinise exactly how creativity occurs in artificial entities by providing appropriate conceptual elements and vocabulary, while experiments enable us to test and confirm the effectiveness of different design decisions considering individual artificial creative entities and their interaction with each other. We propose three novel, domain-general analysis tools for artificial creative entities, i.e. creative systems and creative agents, and collections of them, called creative societies. First, we distinguish several conceptual components relevant for metacreative systems, i.e. systems that can reflect and control their creative behaviour, and discuss how these components are interlinked and affect the system's creativity. Second, we merge elements from sequential decision making in intelligent agents, i.e. Markov Decision Processes, into formal creativity as search model called the Creative Systems Framework, providing a detailed account of various elements which compose the decision-making process of a creative agent. Third, we map elements from an eminent social creativity theory, the Systems View of Creativity, a.k.a. Domain-Individual-Field-Interaction model, into the elements of the Creative Systems Framework and show how creative societies may be analysed formally with it. Each of the proposed analysis tools provides new ways to analyse creativity in artificial entities. The analysis of metacreative systems assumes an architectural point of view to creativity, which has not been previously addressed in detail. Deconstructing the decision-making process of a creative agent gives us additional means to discuss and understand why or how a creative agent selects certain actions. Lastly, the contributions to the creative societies are the first formal framework for their analysis. We also investigate in two consecutive case studies collaborator selection in creative societies. In the first study, we focus on what kind of cues, e.g. selfish or altruistic, assist in choosing beneficial collaboration partners when all the agents can observe from their peers are the individually created end products. The second study allows the agents to adjust their aesthetic preferences during the simulations and inspects what emerges from society as a whole. We conclude that selfish cues seem to be more effective in choosing the collaboration partners in our settings and that the society exhibits distinct emergence depending on how much the agents are willing to change their aesthetic preferences.Luovuus on monitahoinen ilmiö, jonka osatekijöitä voidaan tunnistaa monissa eri asiayhteyksissä. Tässä väitöskirjassa käsitellään laskennallista luovuutta, eli luovuutta koneissa, mikä voidaan karkeasti luokitella tekoälyn yhdeksi osa-alueeksi. Yksi laskennallisen luovuuden tärkeimmistä kiinnostuksen kohteista tutkii miten koneet voivat olla luovia omasta ansiostaan. Tämä tarkoittaa että luovat järjestelmät ja toimijat, menetelmät, yhteisöt sekä niiden vuorovaikutus voivat erota ihmisten vastaavista. On siis tärkeää kyetä keskustelemaan luovien järjestelmien, toimijoiden ja yhteisöjen ominaisuuksista riippumatta niiden toteutuksien yksityiskohdista sekä suunnittelemaan simulaatioita ja kokeita joissa voidaan todentaa suunnitteluratkaisujen vaikutukset järjestelmän luovuudelle. Väitöskirja esittelee kolme uutta luovuuden analyysimenetelmää, jotka on kehitetty analysoimaan (1) luovia järjestelmiä, (2) luovia toimijoita sekä (3) luovia agenttiyhteisöjä. Lisäksi kahdessa osajulkaisussa tutkitaan yhteistyöprosesseja simuloiduissa yhteisöissä, joissa itsenäiset luovat toimijat tuottavat abstraktia taidetta evolutiivisia menetelmiä käyttäen. Ehdotetut analyysimenetelmät mahdollistavat luovuuden monialaisen tarkastelun sekä tarjoavat yhden mahdollisen suunnan kohti laskennallisen luovuuden yhtenäistä analyysimenetelmää. Havainnot empiirisistä simulaatioista antavat uutta tietoa laskennallisista yhteistyöprosesseista ja ovat askel kohti monimutkaisempia kokeita luovan yhteistyön saralla

Towards Goal-aware Collaboration in Artistic Agent Societies

We study the effects of goal-awareness in artistic agent societies creating evolutionary art. Particularly, we examine how goal-awareness may be utilized in modeling agent's peers when the aesthetic goals of the agent and its peers are subject to change. The agents use the learned peer models to choose their collaboration partners, and may alter their own aesthetic goal for the duration of the collaboration in order to enhance the potential of the collaboration outcomes. In addition, we demonstrate how goal-awareness can be used to guide the aesthetic goal change. The empirical evaluation indicates that agents which can adapt to their collaboration partners are more likely to reach favorable collaboration outcomes, even when their partners perceive fundamentally different properties from the artifacts.Peer reviewe

A Feature-Based Call Graph Distance Measure for Program Similarity Analysis

A measurement for how similar (or distant) two computer programs are has a wide range of possible applications. For example, they can be applied to malware analysis or analysis of university students' programming exercises. However, as programs may be arbitrarily structured, capturing the similarity of two non-trivial programs is a complex task. By extracting call graphs (graphs of caller-callee relationships of the program's functions, where nodes denote functions and directed edges denote function calls) from the programs, the similarity measurement can be changed into a graph problem. Previously, static call graph distance measures have been largely based on graph matching techniques, e.g. graph edit distance or maximum common subgraph, which are known to be costly. We propose a call graph distance measure based on features that preserve some structural information from the call graph without explicitly matching user defined functions together. We define basic properties of the features, several ways to compute the feature values, and give a basic algorithm for generating the features. We evaluate our features using two small datasets: a dataset of malware variants, and a dataset of university students' programming exercises, focusing especially on the former. For our evaluation we use experiments in information retrieval and clustering. We compare our results for both datasets to a baseline, and additionally for the malware dataset to the results obtained with a graph edit distance approximation. In our preliminary results we show that even though the feature generation approach is simpler than the graph edit distance approximation, the generated features can perform on a similar level as the graph edit distance approximation. However, experiments on larger datasets are still required to verify the results

Action Selection in the Creative Systems Framework

The Creative Systems Framework (CSF) formalises creativity as search through a space of concepts. As a formal account of Margaret Boden’s descriptive hierarchy of creativity, it is at the basis of multiple studies dealing with diverse aspects of Computational Creativity (CC) systems. However, the CSF at present neither formalises action nor action selection during search, limiting its use in analysing creative processes. We extend the CSF by explicitly modelling these missing components in the search space traversal function. We furthermore introduce a distinction between a concept and its material realisation as an artefact, and elaborate the action selection process to provide stopping criteria for creative search. Our extension, the Creative Action Selection Framework (CASF), is informed by previous studies in CC and draws on concepts from Markov Decision Processes (MDP). It allows us to describe a creative system as an agent selecting actions based on the value, validity and novelty of concepts and artefacts. The CASF brings the descriptive power of the CSF to a wider range of systems with more analytical depth.Peer reviewe

Uutuutta etsivät moniagenttijärjestelmät

This paper considers novelty-seeking multi-agent systems as a step towards more efficient generation of creative artifacts. We describe a simple multi-agent architecture where agents have limited resources and exercise self-criticism, veto power and voting to collectively regulate which artifacts are selected to the domain i.e., the cultural storage of the system. To overcome their individual resource limitations, agents have a limited access to the artifacts already in the domain which they can use to guide their search for novel artifacts. Creating geometric images called spirographs as a case study, we show that novelty-seeking multi-agent systems can be more productive in generating novel artifacts than a single-agent or monolithic system. In particular, veto power is in our case an effective collaborative decision-making strategy for enhancing novelty of domain artifacts, and self-criticism of agents can significantly reduce the collaborative effort in decision making.Peer reviewe

How to Report the Contributions of a CC System?

We argue that the lack of well established reporting practices for applied Computational Creativity systems is hindering progress in the field. We consider that the current lack of reporting details – and variation in form and content – makes it difficult for third parties to reliably evaluate and compare systems based on pub-licly available information. This hinders forming an un-derstanding of the similarities, differences and relative qualities of these systems. We propose a set of building blocks for robustly reporting the contributions of computationally creative systems to promote visibility and clarity in the field.Peer reviewe

On the Inherent Creativity of Self-Adaptive Systems

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.Peer reviewe

Aspects of Self-awareness: An Anatomy of Metacreative Systems

We formulate a model of computational metacreativity. It consists of various aspects of creative self-awareness that potentially contribute, in various combinations, to the metacreative capabilities of a creative system. Our model is inspired by a psychological view of metacreativity promoting the awareness of one's thoughts during the creative process, and draws from the field of self-adaptive software systems to explicate different viewpoints of metacreativity in creative systems. The model is designed to help in analyzing metacreative capabilities of creative systems, and to guide the development of creative systems to a more autonomous and adaptive direction.Peer reviewe

Towards novel and intentional cooperation of diverse autonomous robots : An architectural approach

Publisher Copyright: © 2021 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).In most autonomous robot approaches, the individual robot’s goals and cooperation behavior are fixed during the design. Moreover, the robot’s design may limit its ability to perform other than initially planned tasks. This leaves little room for novel dynamic cooperation where new (joint) actions could be formed or goals adjusted after deployment. In this paper, we address how situational context augmented with peer modeling can foster cooperation opportunity identification and cooperation planning. As a practical contribution, we introduce our new software architecture that enables developing, training, testing, and deploying dynamic cooperation solutions for diverse autonomous robots. The presented architecture operates in three different worlds: in the Real World with real robots, in the 3D Virtual World by emulating the real environments and robots, and in an abstract 2D Block World that fosters developing and studying large-scale cooperation scenarios. Feedback loops among these three worlds bring data from one world to another and provide valuable information to improve cooperation solutions.Peer reviewe

How Does Embodiment Affect the Human Perception of Computational Creativity? An Experimental Study Framework

Which factors influence the human assessment of creativity exhibited by a computational system is a core question of computational creativity (CC) research. Recently, the system’s embodiment has been put forward as such a factor, but empirical studies of its effect are lacking. To this end, we propose an experimental framework which isolates the effect of embodiment on the perception of creativity from its effect on creativity per se. We manipulate not only the system’s embodiment but also the human perception of creativity, which we factorise into the assessment of creativity, and the perceptual evidence that feeds into that assessment. We motivate the core framework with embodiment and perceptual evidence as independent and the creative process as a controlled variable, and we provide recommendations on measuring the assessment of creativity as a dependent variable. We propose three types of perceptual evidence with respect to the creative system, the creative process and the creative artefact, borrowing from the popular four perspectives on creativity. We hope the framework will inspire and guide others to study the human perception of embodied CC in a principled manner.Peer reviewe