33,864 research outputs found
Shallow decision-making analysis in General Video Game Playing
The General Video Game AI competitions have been the testing ground for
several techniques for game playing, such as evolutionary computation
techniques, tree search algorithms, hyper heuristic based or knowledge based
algorithms. So far the metrics used to evaluate the performance of agents have
been win ratio, game score and length of games. In this paper we provide a
wider set of metrics and a comparison method for evaluating and comparing
agents. The metrics and the comparison method give shallow introspection into
the agent's decision making process and they can be applied to any agent
regardless of its algorithmic nature. In this work, the metrics and the
comparison method are used to measure the impact of the terms that compose a
tree policy of an MCTS based agent, comparing with several baseline agents. The
results clearly show how promising such general approach is and how it can be
useful to understand the behaviour of an AI agent, in particular, how the
comparison with baseline agents can help understanding the shape of the agent
decision landscape. The presented metrics and comparison method represent a
step toward to more descriptive ways of logging and analysing agent's
behaviours
The Fraunhofer Quantum Computing Portal - www.qc.fraunhofer.de - A web-based Simulator of Quantum Computing Processes
Fraunhofer FIRST develops a computing service and collaborative workspace
providing a convenient tool for simulation and investigation of quantum
algorithms. To broaden the twenty qubit limit of workstation-based simulations
to the next qubit decade we provide a dedicated high memorized Linux cluster
with fast Myrinet interconnection network together with a adapted parallel
simulator engine. This simulation service supplemented by a collaborative
workspace is usable everywhere via web interface and integrates both hardware
and software as collaboration and investigation platform for the quantum
community. The beta test version realizes all common one, two and three qubit
gates, arbitrary one and two bit gates, orthogonal measurements as well as
special gates like Oracle, Modulo function, Quantum Fourier Transformation and
arbitrary Spin-Hamiltonians up to 31 qubits. For a restricted gate set it
feasible to investigate circuits with up to sixty qubits. URL:
http://www.qc.fraunhofer.d
Engineering Resilient Collective Adaptive Systems by Self-Stabilisation
Collective adaptive systems are an emerging class of networked computational
systems, particularly suited in application domains such as smart cities,
complex sensor networks, and the Internet of Things. These systems tend to
feature large scale, heterogeneity of communication model (including
opportunistic peer-to-peer wireless interaction), and require inherent
self-adaptiveness properties to address unforeseen changes in operating
conditions. In this context, it is extremely difficult (if not seemingly
intractable) to engineer reusable pieces of distributed behaviour so as to make
them provably correct and smoothly composable.
Building on the field calculus, a computational model (and associated
toolchain) capturing the notion of aggregate network-level computation, we
address this problem with an engineering methodology coupling formal theory and
computer simulation. On the one hand, functional properties are addressed by
identifying the largest-to-date field calculus fragment generating
self-stabilising behaviour, guaranteed to eventually attain a correct and
stable final state despite any transient perturbation in state or topology, and
including highly reusable building blocks for information spreading,
aggregation, and time evolution. On the other hand, dynamical properties are
addressed by simulation, empirically evaluating the different performances that
can be obtained by switching between implementations of building blocks with
provably equivalent functional properties. Overall, our methodology sheds light
on how to identify core building blocks of collective behaviour, and how to
select implementations that improve system performance while leaving overall
system function and resiliency properties unchanged.Comment: To appear on ACM Transactions on Modeling and Computer Simulatio
Quantum Robots and Environments
Quantum robots and their interactions with environments of quantum systems
are described and their study justified. A quantum robot is a mobile quantum
system that includes a quantum computer and needed ancillary systems on board.
Quantum robots carry out tasks whose goals include specified changes in the
state of the environment or carrying out measurements on the environment. Each
task is a sequence of alternating computation and action phases. Computation
phase activities include determination of the action to be carried out in the
next phase and possible recording of information on neighborhood environmental
system states. Action phase activities include motion of the quantum robot and
changes of neighborhood environment system states. Models of quantum robots and
their interactions with environments are described using discrete space and
time. To each task is associated a unitary step operator T that gives the
single time step dynamics. T = T_{a}+T_{c} is a sum of action phase and
computation phase step operators. Conditions that T_{a} and T_{c} should
satisfy are given along with a description of the evolution as a sum over paths
of completed phase input and output states. A simple example of a task carrying
out a measurement on a very simple environment is analyzed. A decision tree for
the task is presented and discussed in terms of sums over phase paths. One sees
that no definite times or durations are associated with the phase steps in the
tree and that the tree describes the successive phase steps in each path in the
sum.Comment: 30 Latex pages, 3 Postscript figures, Minor mathematical corrections,
accepted for publication, Phys Rev
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