Building a Truly Distributed Constraint Solver with JADE

Real life problems such as scheduling meeting between people at different locations can be modelled as distributed Constraint Satisfaction Problems (CSPs). Suitable and satisfactory solutions can then be found using constraint satisfaction algorithms which can be exhaustive (backtracking) or otherwise (local search). However, most research in this area tested their algorithms by simulation on a single PC with a single program entry point. The main contribution of our work is the design and implementation of a truly distributed constraint solver based on a local search algorithm using Java Agent DEvelopment framework (JADE) to enable communication between agents on different machines. Particularly, we discuss design and implementation issues related to truly distributed constraint solver which might not be critical when simulated on a single machine. Evaluation results indicate that our truly distributed constraint solver works well within the observed limitations when tested with various distributed CSPs. Our application can also incorporate any constraint solving algorithm with little modifications.Comment: 7 page

Efficient size estimation and impossibility of termination in uniform dense population protocols

We study uniform population protocols: networks of anonymous agents whose pairwise interactions are chosen at random, where each agent uses an identical transition algorithm that does not depend on the population size $n$. Many existing polylog$(n)$ time protocols for leader election and majority computation are nonuniform: to operate correctly, they require all agents to be initialized with an approximate estimate of $n$ (specifically, the exact value $\lfloor \log n \rfloor$). Our first main result is a uniform protocol for calculating $\log(n) \pm O(1)$ with high probability in $O(\log^2 n)$ time and $O(\log^4 n)$ states ($O(\log \log n)$ bits of memory). The protocol is converging but not terminating: it does not signal when the estimate is close to the true value of $\log n$. If it could be made terminating, this would allow composition with protocols, such as those for leader election or majority, that require a size estimate initially, to make them uniform (though with a small probability of failure). We do show how our main protocol can be indirectly composed with others in a simple and elegant way, based on the leaderless phase clock, demonstrating that those protocols can in fact be made uniform. However, our second main result implies that the protocol cannot be made terminating, a consequence of a much stronger result: a uniform protocol for any task requiring more than constant time cannot be terminating even with probability bounded above 0, if infinitely many initial configurations are dense: any state present initially occupies $\Omega(n)$ agents. (In particular, no leader is allowed.) Crucially, the result holds no matter the memory or time permitted. Finally, we show that with an initial leader, our size-estimation protocol can be made terminating with high probability, with the same asymptotic time and space bounds.Comment: Using leaderless phase cloc

An Approach to Model Checking of Multi-agent Data Analysis

The paper presents an approach to verification of a multi-agent data analysis algorithm. We base correct simulation of the multi-agent system by a finite integer model. For verification we use model checking tool SPIN. Protocols of agents are written in Promela language and properties of the multi-agent data analysis system are expressed in logic LTL. We run several experiments with SPIN and the model.Comment: In Proceedings MOD* 2014, arXiv:1411.345

Distributed anonymous function computation in information fusion and multiagent systems

We propose a model for deterministic distributed function computation by a network of identical and anonymous nodes, with bounded computation and storage capabilities that do not scale with the network size. Our goal is to characterize the class of functions that can be computed within this model. In our main result, we exhibit a class of non-computable functions, and prove that every function outside this class can at least be approximated. The problem of computing averages in a distributed manner plays a central role in our development

A Reinforcement Learning Agent for Minutiae Extraction from Fingerprints

In this paper we show that reinforcement learning can be used for minutiae detection in fingerprint matching. Minutiae are characteristic features of fingerprints that determine their uniqueness. Classical approaches use a series of image processing steps for this task, but lack robustness because they are highly sensitive to noise and image quality. We propose a more robust approach, in which an autonomous agent walks around in the fingerprint and learns how to follow ridges in the fingerprint and how to recognize minutiae. The agent is situated in the environment, the fingerprint, and uses reinforcement learning to obtain an optimal policy. Multi-layer perceptrons are used for overcoming the difficulties of the large state space. By choosing the right reward structure and learning environment, the agent is able to learn the task. One of the main difficulties is that the goal states are not easily specified, for they are part of the learning task as well. That is, the recognition of minutiae has to be learned in addition to learning how to walk over the ridges in the fingerprint. Results of successful first experiments are presented

Changes in neuromuscular structure and functions of human colon during ageing are region-dependent

Objective: To determine if human colonic neuromuscular functions decline with increasing age.Design: Looking for non-specific changes in neuromuscular function, a standard burst of electrical field stimulation (EFS) was used to evoke neuronally mediated (cholinergic/nitrergic) contractions/relaxations in ex vivomuscle strips of human ascending and descending colon, aged 35–91 years (macroscopically normal tissue; 239 patients undergoing cancer resection). Then, to understand mechanisms of change, numbers and phenotype of myenteric neurons (30 306 neurons stained with different markers), densities of intramuscular nerve fibres (51 patients in total) and pathways involved in functional changes were systematically investigated (by immunohistochemistry and use of pharmacological tools) in elderly (≥70 years) and adult (35–60 years) groups.Results: With increasing age, EFS was more likely to evoke muscle relaxation in ascending colon instead of contraction (linear regression: n=109, slope 0.49%±0.21%/year, 95% CI ), generally uninfluenced by comorbidity or use of medications. Similar changes were absent in descending colon. In the elderly, overall numbers of myenteric and neuronal nitric oxide synthaseimmunoreactive neurons and intramuscular nerve densities were unchanged in ascending and descending colon, compared with adults. In elderly ascending, not descending, colon numbers of cell bodies exhibiting choline acetyltransferase immunoreactivity increased compared with adults (5.0±0.6 vs 2.4±0.3 neurons/mm myenteric plexus, p=0.04). Cholinergically mediated contractions were smaller in elderly ascending colon compared with adults (2.1±0.4 and 4.1±1.1 g-tension/gtissue during EFS; n=25/14; p=0.04); there were no changes in nitrergic function or in ability of the muscle to contract/relax. Similar changes were absent in descending colon.Conclusion: In ascending not descending colon, ageing impairs cholinergic function