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Missão

A missão do DEI é contribuir para o desenvolvimento da sociedade, promovendo um ensino superior de excelência na área da Engenharia Informática, nas vertentes de graduação e pós-graduação, levando para tal a cabo actividades de Investigação, Desenvolvimento e Inovação ao nível dos mais elevados padrões internacionais.


Anúncios

Provas de Agregação em Engenharia Informática e de Computadores

22 Junho 2018, 12:39 - Fátima Sampaio


Candidato: Doutor Miguel Leitão Bignolas Mira da Silva

Relatório da Unidade Curricular: IT Govemance

Seminário: Using Models for Implementing IT Govemance Practices

Local da Prova: Anfiteatro PA-3 (Piso -1, Pavilhão de Matemática) IST, Alameda

Data: 16/07/2018 e 17/07/2018

Hora: 14h30




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Eventos

Prova de Doutoramento

22 Junho 2018, 16:58 - Fátima Sampaio


Candidate: Fernando Pedro Pascoal dos Santos Nº 64757

Title: Dynamics of Reputation and the Self-organization of Cooperation 

Date: 29/06/2018

Time: 12:15

Location: Sala de Reuniões do Departamento de Engenharia Informática (0.19), Pavilhão de Informática II do IST, Alameda 

Supervisor: Professor Francisco João Duarte Cordeiro Correia dos Santos

Co-Supervisors: Professora Ana Maria Severino de Almeida e Paiva / Professor Jorge Manuel dos Santos Pacheco

Abstract: Indirect Reciprocity (IR) – Alice behaves adequately towards Bob; Carol knows about it and thus helps Alice – is a central mechanism to explain human cooperation. IR involves reputation, status and complex information processing, being the most specifically human of all cooperation mechanisms discovered to date. Understanding evolutionary dynamics under IR can shed light on human social behaviors and morality. Simultaneously, IR can inform about ways of engineering cooperation in new one-shot interaction paradigms where reputations are central – such as web-based platforms or, with the advent of Artificial Intelligence, agent-agent and human-agent interactions.In this thesis we develop a formulation of IR to deal with populations of finite sizeand, in this context, investigate the limits of IR in promoting cooperation along several nonexcluding directions. We start by exploring the stochastic dynamics of IR employing na analytical framework that relies on the assumption that exploration rates – the likelihood of spontaneously adopting another strategy – are low. Subsequently, we develop a computational model to simulate, visualize and investigate the evolutionary dynamics, under IR, of populations of finite size and at arbitrary exploration rates. This allows us to study, originally, the impact of two key features of human social interactions: (i) costly reputation building, whereby individuals may decide to pay a cost to share the outcome of a private interaction; (ii) high order social norms, including the past reputations of individuals (fourth-order under the existing IR hierarchical classification). The complexity of both norms and strategies involved in (ii) called for the development of a new paradigm in assessing information exchange and processing in IR. To this end, we propose a new means of quantifying the complexity of both norms and strategies, resorting to concepts rooted in Boolean algebra.Employing these new methodologies, we conclude that (i) the leading norms capable of promoting cooperation, not only depend sensitively on the population size, but also they may be affected by high exploration rates, which may both improve and harm cooperation, depending on the social norm at work; (ii) under costly reputation building, cooperation depends on the ability of individuals to anticipate accurately the reporting intention of their peers. Finally, we identify a key pattern of fourth-order norms that constitutes a necessary condition for a norm to promote cooperation. We show that, out of 216 possible norms, there exists one very simple norm that complies with this pattern, promoting high levels of cooperation while ignoring the previous reputation of individuals.


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