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Abstract: While AI has recently produced impressive systems that achieve human-like performance at challenging tasks, these systems tell us very little about how human intelligence works. In particular, they do not address the problem of composing knowledge and behaviour incrementally – a phenomenon that is pervasive in individual and collective human intelligence. We argue that achieving more human-like AI requires focusing on diversity in reasoning and behaviour among humans and artificial agents, and that developing systems capable of dealing with such diversity is key to achieving more human-like AI. In these systems intelligence should not only be measured in terms of how a system performs at a certain task, but also in terms of the properties of the process by which each component combines its knowledge and behaviour with that of others, just like humans do.

Citation: M. Rovatsos. Diversity-Awareness – The Key to Human-Like Computing? In S. Muggleton et al, editor, Twentieth Workshop on Machine Intelligence (MI 20), Windsor Park, UK, 23-25 October, 2016. In press.

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Abstract: Collective adaptive systems (CASs) have been researched intensively since many years. However, the recent emerging developments and advanced models in service-oriented computing, cloud computing and human computation have fostered several new forms of CASs. Among them, Hybrid and Diversity-aware CASs (HDA-CASs) characterize new types of CASs in which a collective is composed of hybrid machines and humans that collaborate together with different complementary roles. This emerging HDA-CAS poses several research challenges in terms of programming, management and provisioning. In this paper, we investigate the main issues in programming HDA-CASs. First, we analyze context characterizing HDA-CASs. Second, we propose to use the concept of hybrid compute units to implement HDA-CASs that can be elastic. We call this type of HDA-CASs h2h2 CAS (Hybrid Compute Unit-based HDA-CAS). We then discuss a meta-view of h2h2 CAS that describes a h2h2 CAS program. We analyze and present program features for h2h2 CAS in four main different contexts.

Citation: Hong-Linh Truong, Schahram Dustdar, “Context-aware Programming for Hybrid and Diversity-aware Collective Adaptive Systems”, Springer, International Workshop on Business Processes in Collective Adaptive Systems (BPCAS 2014), 12th Intl. Conf. on Business Process Management (BPM14), Eindhoven, The Netherlands, September 7-12, 2014

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You can find the workshop proceeedings on the ECAI website, or directly download them from here.

To get a glimpse of what the day was like, you can follow #diversityAwareAI on Twitter.

Michael Rovatsos opens DIVERSITY 2016 with a quote from Marvin Minsky.

Marvin Minsky: “What magical trick makes us intelligent? The trick is that there is no trick. The power of intelligence stems from our vast diversity, not from any single, perfect principle.”

Abstract. The physical and virtual dimensions of life are becoming more and more deeply interwoven. Society is merging with technology, giving rise to a global socio-technical ecosystem. In a society comprising people and machines as actors we often see people-to-people interactions mediated by machine and machine-to-machine interaction mediated by people. The speed and scale of this change and the differences in culture, language and interests make the problem of establishing effective means of communication and coordination increasingly challenging. Our vision, embodied in the SmartSociety project1, is that a new generation of systems, hybrid (i.e., including humans and artificial peers, as well as social groups), distributed, open and large-scale, is needed to tackle these issues. In such systems, multitudes of heterogeneous peers will produce and handle massive amounts of data; peers will join/leave the system following unpredictable patterns with no central coordination and will interoperate at different spatial and temporal scales. Aware of the ethical issues, and by identifying the right incentive schemes and privacy levels, these systems will assist individuals and collectives in their everyday activities, coping with the diversity of the world and working in the presence of incomplete and incorrect information.

http://eprints.biblio.unitn.it/4214/

Citation: F. Giunchiglia, V. Maltese, S. Anderson, D. Miorandi (2013). Towards Hybrid and Diversity-Aware Collective Adaptive Systems. First FOCAS Workshop on Fundamentals of Collective Systems @ECAL 2013.

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