772,136 research outputs found
Collective Motion of Predictive Swarms
Theoretical models of populations and swarms typically start with the
assumption that the motion of agents is governed by the local stimuli. However,
an intelligent agent, with some understanding of the laws that govern its
habitat, can anticipate the future, and make predictions to gather resources
more efficiently. Here we study a specific model of this kind, where agents aim
to maximize their consumption of a diffusing resource, by attempting to predict
the future of a resource field and the actions of other agents. Once the agents
make a prediction, they are attracted to move towards regions that have, and
will have, denser resources. We find that the further the agents attempt to see
into the future, the more their attempts at prediction fail, and the less
resources they consume. We also study the case where predictive agents compete
against non-predictive agents and find the predictors perform better than the
non-predictors only when their relative numbers are very small. We conclude
that predictivity pays off either when the predictors do not see too far into
the future or the number of predictors is small.Comment: 16 pages, 7 figure
Propagators and Violation Functions for Geometric and Workload Constraints Arising in Airspace Sectorisation
Airspace sectorisation provides a partition of a given airspace into sectors,
subject to geometric constraints and workload constraints, so that some cost
metric is minimised. We make a study of the constraints that arise in airspace
sectorisation. For each constraint, we give an analysis of what algorithms and
properties are required under systematic search and stochastic local search
Diagonal Peg Solitaire
We study the classical game of peg solitaire when diagonal jumps are allowed.
We prove that on many boards, one can begin from a full board with one peg
missing, and finish with one peg anywhere on the board. We then consider the
problem of finding solutions that minimize the number of moves (where a move is
one or more jumps by the same peg), and find the shortest solution to the
"central game", which begins and ends at the center. In some cases we can prove
analytically that our solutions are the shortest possible, in other cases we
apply A* or bidirectional search heuristics.Comment: 20 pages, 11 figure
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