Coordination with Humans via Strategy Matching

Human and robot partners increasingly need to work together to perform tasks as a team. Robots designed for such collaboration must reason about how their task-completion strategies interplay with the behavior and skills of their human team members as they coordinate on achieving joint goals. Our goal in this work is to develop a computational framework for robot adaptation to human partners in human-robot team collaborations. We first present an algorithm for autonomously recognizing available task-completion strategies by observing human-human teams performing a collaborative task. By transforming team actions into low dimensional representations using hidden Markov models, we can identify strategies without prior knowledge. Robot policies are learned on each of the identified strategies to construct a Mixture-of-Experts model that adapts to the task strategies of unseen human partners. We evaluate our model on a collaborative cooking task using an Overcooked simulator. Results of an online user study with 125 participants demonstrate that our framework improves the task performance and collaborative fluency of human-agent teams, as compared to state of the art reinforcement learning methods.Comment: 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2022

Design Considerations for Real-Time Collaboration with Creative Artificial Intelligence

Machines incorporating techniques from artificial intelligence and machine learning can work with human users on a moment-to-moment, real-time basis to generate creative outcomes, performances and artefacts. We define such systems collaborative, creative AI systems, and in this article, consider the theoretical and practical considerations needed for their design so as to support improvisation, performance and co-creation through real-time, sustained, moment-to-moment interaction. We begin by providing an overview of creative AI systems, examining strengths, opportunities and criticisms in order to draw out the key considerations when designing AI for human creative collaboration. We argue that the artistic goals and creative process should be first and foremost in any design. We then draw from a range of research that looks at human collaboration and teamwork, to examine features that support trust, cooperation, shared awareness and a shared information space. We highlight the importance of understanding the scope and perception of two-way communication between human and machine agents in order to support reflection on conflict, error, evaluation and flow. We conclude with a summary of the range of design challenges for building such systems in provoking, challenging and enhancing human creative activity through their creative agency

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

Measuring architectural adaptability in i* models

Developing adaptable systems is still a big challenge in software engineering. Different reference architectures and systematic approaches have been proposed to address this challenge. Several of these approaches are based on goal models, given their suitability to express and reason on alternative behaviors. In this paper we intend to provide a basis for comparing architectures described in goal-based models in regard to their adaptability. This way, different approaches to improve adaptability may be compared based on the resulting architectures. To do so we mapped two adaptability metrics onto i* models and developed guidelines to define the adaptability of individual elements, based on the extra information provided by i* models. We applied these metrics in a healthcare system to illustrate the comparison of architectures.Peer ReviewedPostprint (published version

A systematic methodology to analyse the performance and design configurations of business interoperability in cooperative industrial networks

This thesis proposes a methodology for modelling business interoperability in a context of cooperative industrial networks. The purpose is to develop a methodology that enables the design of cooperative industrial network platforms that are able to deliver business interoperability and the analysis of its impact on the performance of these platforms. To achieve the proposed objective, two modelling tools have been employed: the Axiomatic Design Theory for the design of interoperable platforms; and Agent-Based Simulation for the analysis of the impact of business interoperability. The sequence of the application of the two modelling tools depends on the scenario under analysis, i.e. whether the cooperative industrial network platform exists or not. If the cooperative industrial network platform does not exist, the methodology suggests first the application of the Axiomatic Design Theory to design different configurations of interoperable cooperative industrial network platforms, and then the use of Agent-Based Simulation to analyse or predict the business interoperability and operational performance of the designed configurations. Otherwise, one should start by analysing the performance of the existing platform and based on the achieved results, decide whether it is necessary to redesign it or not. If the redesign is needed, simulation is once again used to predict the performance of the redesigned platform. To explain how those two modelling tools can be applied in practice, a theoretical modelling framework, a theoretical Axiomatic Design model and a theoretical Agent-Based Simulation model are proposed. To demonstrate the applicability of the proposed methodology and/or to validate the proposed theoretical models, a case study regarding a Portuguese Reverse Logistics cooperative network (Valorpneu network) and a case study regarding a Portuguese construction project (Dam Baixo Sabor network) are presented. The findings of the application of the proposed methodology to these two case studies suggest that indeed the Axiomatic Design Theory can effectively contribute in the design of interoperable cooperative industrial network platforms and that Agent-Based Simulation provides an effective set of tools for analysing the impact of business interoperability on the performance of those platforms. However, these conclusions cannot be generalised as only two case studies have been carried out. In terms of relevance to theory, this is the first time that the network effect is addressed in the analysis of the impact of business interoperability on the performance of networked companies and also the first time that a holistic approach is proposed to design interoperable cooperative industrial network platforms. Regarding the practical implications, the proposed methodology is intended to provide industrial managers a management tool that can guide them easily, and in practical and systematic way, in the design of configurations of interoperable cooperative industrial network platforms and/or in the analysis of the impact of business interoperability on the performance of their companies and the networks where their companies operate

Entering the KIBS' black box: there must be an angel! (or is there something like a knowledge angel?)

The undeniable importance of knowledge and innovation in modern economies justifies the increasing interest that scholars are taking in studying knowledge-intensive busi-ness services (KIBS). Since the mid 1990s, there has been a significant increase in the attention paid to KIBS and their role and functions in innovation systems (den Hertog 2000; Illeris 1991; Miles et al. 1995; Muller/Zenker 2001; Strambach 2001; Tether 2005; Wood 2002). In general terms, the activity of KIBS can be mainly described as the provision of knowledge-intensive inputs to the business process of other organiza-tions, private as well as public sector clients. [...] To sum up, this paper focuses on creative individuals in KIBS, i.e. those persons sus-pected of playing a pertinent role with respect to the innovativeness of their company. We call these specific actors knowledge angels by analogy with business angels. In the same way that business angels can play a decisive role in the development of innova-tive firms through financial support, we assume here that specifically gifted persons can be the knowledge 'catalysts' within KIBS (and in relationship with their clients). The paper contains three sections: the first one formulates the assumption of the exis-tence of knowledge angels and attempts to elaborate a working definition of this spe-cific kind of actor. The second section displays the results of an empirical research pro-ject conducted in France and Germany, whereas the third section synthesizes the find-ings. --