145,655 research outputs found
Infrastructure transitions toward sustainability: a complex adaptive systems perspective
To ensure infrastructure assets are procured and maintained by government on behalf of citizens, appropriate policy and institutional architecture is needed, particularly if a fundamental shift to more sustainable infrastructure is the goal. The shift in recent years from competitive and resource-intensive procurement to more collaborative and sustainable approaches to infrastructure governance is considered a major transition in infrastructure procurement systems. In order to better understand this transition in infrastructure procurement arrangements, the concept of emergence from Complex Adaptive Systems (CAS) theory is offered as a key construct. Emergence holds that micro interactions can result in emergent macro order. Applying the concept of emergence to infrastructure procurement, this research examines how interaction of agents in individual projects can result in different industry structural characteristics. The paper concludes that CAS theory, and particularly the concept of ‘emergence’, provides a useful construct to understand infrastructure procurement dynamics and progress towards sustainability
Vehicle Based Intersection Management with Intelligent Agents
Signal-based intersection management will change when vehicles with intelligent capability are available in the future. Intelligent agents embedded in vehicle software will be responsible for vehicle control and route guidance. Intersection management can be achieved through the collaboration of these agents, without a centralized control infrastructure. This research focuses on the use of distributed multi-agent systems to provide microscopic adaptive control which might reduce traffic delay and chances of collisions at intersections. A hypothesized Mobile Ad-hoc Network provides communication links to connect the agents.Intelligent Agents, Adaptive Intersection Control
Evolutionary establishment of moral and double moral standards through spatial interactions
Situations where individuals have to contribute to joint efforts or share
scarce resources are ubiquitous. Yet, without proper mechanisms to ensure
cooperation, the evolutionary pressure to maximize individual success tends to
create a tragedy of the commons (such as over-fishing or the destruction of our
environment). This contribution addresses a number of related puzzles of human
behavior with an evolutionary game theoretical approach as it has been
successfully used to explain the behavior of other biological species many
times, from bacteria to vertebrates. Our agent-based model distinguishes
individuals applying four different behavioral strategies: non-cooperative
individuals ("defectors"), cooperative individuals abstaining from punishment
efforts (called "cooperators" or "second-order free-riders"), cooperators who
punish non-cooperative behavior ("moralists"), and defectors, who punish other
defectors despite being non-cooperative themselves ("immoralists"). By
considering spatial interactions with neighboring individuals, our model
reveals several interesting effects: First, moralists can fully eliminate
cooperators. This spreading of punishing behavior requires a segregation of
behavioral strategies and solves the "second-order free-rider problem". Second,
the system behavior changes its character significantly even after very long
times ("who laughs last laughs best effect"). Third, the presence of a number
of defectors can largely accelerate the victory of moralists over non-punishing
cooperators. Forth, in order to succeed, moralists may profit from immoralists
in a way that appears like an "unholy collaboration". Our findings suggest that
the consideration of punishment strategies allows to understand the
establishment and spreading of "moral behavior" by means of game-theoretical
concepts. This demonstrates that quantitative biological modeling approaches
are powerful even in domains that have been addressed with non-mathematical
concepts so far. The complex dynamics of certain social behaviors becomes
understandable as result of an evolutionary competition between different
behavioral strategies.Comment: 15 pages, 5 figures; accepted for publication in PLoS Computational
Biology [supplementary material available at
http://www.soms.ethz.ch/research/secondorder-freeriders/ and
http://www.matjazperc.com/plos/moral.html
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