7,686 research outputs found
Artificial life meets computational creativity?
I review the history of work in Artificial Life on the problem of the open-ended evolutionary growth of complexity in computational worlds. This is then put into the context of evolutionary epistemology and human creativity
Synchronization Strings: Explicit Constructions, Local Decoding, and Applications
This paper gives new results for synchronization strings, a powerful
combinatorial object that allows to efficiently deal with insertions and
deletions in various communication settings:
We give a deterministic, linear time synchronization string
construction, improving over an time randomized construction.
Independently of this work, a deterministic time
construction was just put on arXiv by Cheng, Li, and Wu. We also give a
deterministic linear time construction of an infinite synchronization string,
which was not known to be computable before. Both constructions are highly
explicit, i.e., the symbol can be computed in time.
This paper also introduces a generalized notion we call
long-distance synchronization strings that allow for local and very fast
decoding. In particular, only time and access to logarithmically
many symbols is required to decode any index.
We give several applications for these results:
For any we provide an insdel correcting
code with rate which can correct any fraction
of insdel errors in time. This near linear computational
efficiency is surprising given that we do not even know how to compute the
(edit) distance between the decoding input and output in sub-quadratic time. We
show that such codes can not only efficiently recover from fraction of
insdel errors but, similar to [Schulman, Zuckerman; TransInf'99], also from any
fraction of block transpositions and replications.
We show that highly explicitness and local decoding allow for
infinite channel simulations with exponentially smaller memory and decoding
time requirements. These simulations can be used to give the first near linear
time interactive coding scheme for insdel errors
Optimal Population Coding, Revisited
Cortical circuits perform the computations underlying rapid perceptual decisions within a few dozen milliseconds with each neuron emitting only a few spikes. Under these conditions, the theoretical analysis of neural population codes is challenging, as the most commonly used theoretical tool – Fisher information – can lead to erroneous conclusions about the optimality of different coding schemes. Here we revisit the effect of tuning function width and correlation structure on neural population codes based on ideal observer analysis in both a discrimination and reconstruction task. We show that the optimal tuning function width and the optimal correlation structure in both paradigms strongly depend on the available decoding time in a very similar way. In contrast, population codes optimized for Fisher information do not depend on decoding time and are severely suboptimal when only few spikes are available. In addition, we use the neurometric functions of the ideal observer in the classification task to investigate the differential coding properties of these Fisher-optimal codes for fine and coarse discrimination. We find that the discrimination error for these codes does not decrease to zero with increasing population size, even in simple coarse discrimination tasks. Our results suggest that quite different population codes may be optimal for rapid decoding in cortical computations than those inferred from the optimization of Fisher information
Alpha Entanglement Codes: Practical Erasure Codes to Archive Data in Unreliable Environments
Data centres that use consumer-grade disks drives and distributed
peer-to-peer systems are unreliable environments to archive data without enough
redundancy. Most redundancy schemes are not completely effective for providing
high availability, durability and integrity in the long-term. We propose alpha
entanglement codes, a mechanism that creates a virtual layer of highly
interconnected storage devices to propagate redundant information across a
large scale storage system. Our motivation is to design flexible and practical
erasure codes with high fault-tolerance to improve data durability and
availability even in catastrophic scenarios. By flexible and practical, we mean
code settings that can be adapted to future requirements and practical
implementations with reasonable trade-offs between security, resource usage and
performance. The codes have three parameters. Alpha increases storage overhead
linearly but increases the possible paths to recover data exponentially. Two
other parameters increase fault-tolerance even further without the need of
additional storage. As a result, an entangled storage system can provide high
availability, durability and offer additional integrity: it is more difficult
to modify data undetectably. We evaluate how several redundancy schemes perform
in unreliable environments and show that alpha entanglement codes are flexible
and practical codes. Remarkably, they excel at code locality, hence, they
reduce repair costs and become less dependent on storage locations with poor
availability. Our solution outperforms Reed-Solomon codes in many disaster
recovery scenarios.Comment: The publication has 12 pages and 13 figures. This work was partially
supported by Swiss National Science Foundation SNSF Doc.Mobility 162014, 2018
48th Annual IEEE/IFIP International Conference on Dependable Systems and
Networks (DSN
A New Class of MDS Erasure Codes Based on Graphs
Maximum distance separable (MDS) array codes are XOR-based optimal erasure
codes that are particularly suitable for use in disk arrays. This paper
develops an innovative method to build MDS array codes from an elegant class of
nested graphs, termed \textit{complete-graph-of-rings (CGR)}. We discuss a
systematic and concrete way to transfer these graphs to array codes, unveil an
interesting relation between the proposed map and the renowned perfect
1-factorization, and show that the proposed CGR codes subsume B-codes as their
"contracted" codes. These new codes, termed \textit{CGR codes}, and their dual
codes are simple to describe, and require minimal encoding and decoding
complexity.Comment: in Proceeding of IEEE Global Communications Conference (GLOBECOM
Performance Modelling and Optimisation of Multi-hop Networks
A major challenge in the design of large-scale networks is to predict and optimise the
total time and energy consumption required to deliver a packet from a source node to a
destination node. Examples of such complex networks include wireless ad hoc and sensor
networks which need to deal with the effects of node mobility, routing inaccuracies, higher
packet loss rates, limited or time-varying effective bandwidth, energy constraints, and the
computational limitations of the nodes. They also include more reliable communication
environments, such as wired networks, that are susceptible to random failures, security
threats and malicious behaviours which compromise their quality of service (QoS) guarantees.
In such networks, packets traverse a number of hops that cannot be determined
in advance and encounter non-homogeneous network conditions that have been largely
ignored in the literature. This thesis examines analytical properties of packet travel in
large networks and investigates the implications of some packet coding techniques on both
QoS and resource utilisation.
Specifically, we use a mixed jump and diffusion model to represent packet traversal
through large networks. The model accounts for network non-homogeneity regarding
routing and the loss rate that a packet experiences as it passes successive segments of a
source to destination route. A mixed analytical-numerical method is developed to compute
the average packet travel time and the energy it consumes. The model is able to capture
the effects of increased loss rate in areas remote from the source and destination, variable
rate of advancement towards destination over the route, as well as of defending against
malicious packets within a certain distance from the destination. We then consider sending
multiple coded packets that follow independent paths to the destination node so as to
mitigate the effects of losses and routing inaccuracies. We study a homogeneous medium
and obtain the time-dependent properties of the packetās travel process, allowing us to
compare the merits and limitations of coding, both in terms of delivery times and energy
efficiency. Finally, we propose models that can assist in the analysis and optimisation
of the performance of inter-flow network coding (NC). We analyse two queueing models
for a router that carries out NC, in addition to its standard packet routing function. The
approach is extended to the study of multiple hops, which leads to an optimisation problem
that characterises the optimal time that packets should be held back in a router, waiting
for coding opportunities to arise, so that the total packet end-to-end delay is minimised
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