6,479 research outputs found
The Markov blankets of life: autonomy, active inference and the free energy principle
This work addresses the autonomous organization of biological systems. It does so by considering the boundaries of biological systems, from individual cells to Home sapiens, in terms of the presence of Markov blankets under the active inference scheme—a corollary of the free energy principle. A Markov blanket defines the boundaries of a system in a statistical sense. Here we consider how a collective of Markov blankets can self-assemble into a global system that itself has a Markov blanket; thereby providing an illustration of how autonomous systems can be understood as having layers of nested and self-sustaining boundaries. This allows us to show that: (i) any living system is a Markov blanketed system and (ii) the boundaries of such systems need not be co-extensive with the biophysical boundaries of a living organism. In other words, autonomous systems are hierarchically composed of Markov blankets of Markov blankets—all the way down to individual cells, all the way up to you and me, and all the way out to include elements of the local environment
Asymptotically idempotent aggregation operators for trust management in multi-agent systems
The study of trust management in
multi-agent system, especially distributed,
has grown over the last
years. Trust is a complex subject
that has no general consensus in literature,
but has emerged the importance
of reasoning about it computationally.
Reputation systems takes
into consideration the history of an
entity’s actions/behavior in order to
compute trust, collecting and aggregating
ratings from members in a
community. In this scenario the aggregation
problem becomes fundamental,
in particular depending on
the environment. In this paper we
describe a technique based on a class
of asymptotically idempotent aggregation
operators, suitable particulary
for distributed anonymous environments
Context-dependent Trust Decisions with Subjective Logic
A decision procedure implemented over a computational trust mechanism aims to
allow for decisions to be made regarding whether some entity or information
should be trusted. As recognised in the literature, trust is contextual, and we
describe how such a context often translates into a confidence level which
should be used to modify an underlying trust value. J{\o}sang's Subjective
Logic has long been used in the trust domain, and we show that its operators
are insufficient to address this problem. We therefore provide a
decision-making approach about trust which also considers the notion of
confidence (based on context) through the introduction of a new operator. In
particular, we introduce general requirements that must be respected when
combining trustworthiness and confidence degree, and demonstrate the soundness
of our new operator with respect to these properties.Comment: 19 pages, 4 figures, technical report of the University of Aberdeen
(preprint version
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