Search results for "Collective Intelligence"
showing 9 items of 29 documents
Integrating Social Skills in Task-Oriented 3D IVA
2005
This paper presents a set of mechanisms oriented to incorporate social information into the decision taking of task-oriented 3DIVA. The aim of this approach is to integrate collaborative skills in different character's roles (seller/buyer, worker, pedestrian, etc.) in order to enhance its behavioral animation. The collective intelligence expected in this kind of multi-character domains (e.g. storytelling, urban simulation, interactive games, etc.) requires agents able to dialogue/interact with other characters, to autonomously group/ungroup (according to their goals), or to distribute tasks and coordinate their execution for solving possible conflicts. The social model implemented follows t…
Modelling swarm-intelligent systems for medical applications
2017
Modeling swarm intelligent systems has attracted attention of researchers over the last decade, as the attributes such as self-organization, self-regulation or collective behavior exhibited by the system entities while following a certain set of rules, can be implemented with the aim at investigating complexity of the problems that an individual would be unable to tackle in real world. In this keynote paper, meta-heuristics and paradigms of modeling swarm-intelligent systems will be discussed with respect to their application areas for medical purposes.
TB-Structure: Collective Intelligence for Exploratory Keyword Search
2017
In this paper we address an exploratory search challenge by presenting a new (structure-driven) collaborative filtering technique. The aim is to increase search effectiveness by predicting implicit seeker’s intents at an early stage of the search process. This is achieved by uncovering behavioral patterns within large datasets of preserved collective search experience. We apply a specific tree-based data structure called a TB (There-and-Back) structure for compact storage of search history in the form of merged query trails – sequences of queries approaching iteratively a seeker’s goal. The organization of TB-structures allows inferring new implicit trails for the prediction of a seeker’s i…
Modelling complex dynamics and distributed generation of knowledge with bacterial-based algorithms
2014
Este estudio tuvo como objetivo demostrar que las sociedades conectadas y heterogéneas con intercambios entre pares (P2P) son más resilientes que las centralizadas y homogéneas. En el modelado basado en agentes, se modelizan agentes con racionalidad limitada que interactúan en un entorno común guiado por reglas locales, lo que lleva a Sistemas Adaptativos Complejos (CAS) que se denominan 'sociedades artificiales'. Estos modelos simplificados de sociedades humanas crecen de abajo hacia arriba en entornos computacionales y pueden utilizarse como un laboratorio para probar algunas hipótesis. Hemos demostrado que en un modelo basado en interacciones libres entre agentes autónomos, los resultado…
Web 2.0 and the collective intelligence
2008
In this paper, I describe a new form of collective intelligence (CI) on the Internet. It is project-like self-organization of masses of ordinary people on the Internet. These crowds emerge, define the collective problem or task by themselves, solve it, and vanish as entities. I have coined this phenomena to netcrowd ('verkkovoima' in Finnish). I compare netcrowd to other forms of CI and suggest a typology for CI types.
Cloning and training collective intelligence with generative adversarial networks
2021
Industry 4.0 and highly automated critical infrastructure can be seen as cyber‐physical‐social systems controlled by the Collective Intelligence. Such systems are essential for the functioning of the society and economy. On one hand, they have flexible infrastructure of heterogeneous systems and assets. On the other hand, they are social systems, which include collaborating humans and artificial decision makers. Such (human plus machine) resources must be pre‐trained to perform their mission with high efficiency. Both human and machine learning approaches must be bridged to enable such training. The importance of these systems requires the anticipation of the potential and previously unknow…
Industry 4.0 vs. Industry 5.0 : Co-existence, Transition, or a Hybrid
2023
Smart manufacturing is being shaped nowadays by two different paradigms: Industry 4.0 proclaims transition to digitalization and automation of processes while emerging Industry 5.0 emphasizes human centricity. This turn can be explained by unprecedented challenges being faced recently by societies, such as, global climate change, pandemics, hybrid and conventional warfare, refugee crises. Sustainable and resilient processes require humans to get back into the loop of organizational decision-making. In this paper, we argue that the most reasonable way to marry the two extremes of automation and value-based human-driven processes is to create an Industry 4.0 + Industry 5.0 hybrid, which inher…
Commoning of territorial heritage and tools of participated sustainability for the production and enhancement of agro-environmental public goods
2021
AbstractThe purpose of this paper is to analyze how the commoning heritage processes find application for the production of agro-environmental public goods in contexts of high socio-economic marginality and environmental vulnerability, characterized by abandonment and from the consumption of agricultural land for food use. The purpose is to understand how these processes are able to influence, at local level, the governance processes for the implementation of environmental protection strategies. The survey made it possible to verify how the commoning processes aimed at the production of agro-environmental goods generate territorial resilience, understood as a community competence able to st…
Protocol: A literature review about the use of crowdsourcing in educational environments
2016
<p>The objective with the protocol described in this paper is to review the existing literature in relation to the implementation of crowdsourcing in educational environments. It seeks to give answer to 4 questions. First, it seeks to answer the question of which kind of crowdsourcing initiatives are more appropriate to be used for educational activities. In second place it’s important to find out whether there is any particular discipline in which crowdsourcing, by its nature, can be applied more naturally. Third, it seeks to identify which factors influence both positively and negatively in the teaching/learning experience using crowdsourcing. Finally, the last question to answer, t…