Search results for "NETWORK"
showing 10 items of 7718 documents
Artificial Intelligence + Distributed Systems = Agents
2009
The connection with Wirth’s book goes beyond the title, albeit confining the area to modern Artificial Intelligence (AI). Whereas thirty years ago, to devise effective programs, it became necessary to enhance the classical algorithmic framework with approaches applied to limited and focused subdomains, in the context of broad-band technology and semantic web, applications - running in open, heterogeneous, dynamic and uncertain environments-current paradigms are not enough, because of the shift from programs to processes. Beside the structure as position paper, to give more weight to some basic assertions, results of recent research are abridged and commented upon in line with new paradigms.…
Optimal Resource Discovery Paths of Gnutella2
2008
This paper shows that the performance of peer-to-peer resource discovery algorithms is upper bounded by a k-Steiner minimum tree and proposes an algorithm locating near-optimal query paths for the peer-to-peer resource discovery problem. Global knowledge of the topology and the resources from the peer-to-peer network are required as an input to the algorithm. The algorithm provides an objective measure for defining how good local search algorithms are. The performance is evaluated in simulated peer-to-peer scenarios and in the measured Gnutella2 P2P network topology with four local search algorithms: breadth-first search, self-avoiding random walker, highest degree search and Dynamic Query …
Social network analysis: the use of graph distances to compare artificial and criminal networks
2021
Aim: Italian criminal groups become more and more dangerous spreading their activities into new sectors. A criminal group is made up of networks of hundreds of family gangs which extended their influence across the world, raking in billions from drug trafficking, extortion and money laundering. We focus in particular on the analysis of the social structure of two Sicilian crime families and we used a Social Network Analysis approach to study the social phenomena. Starting from a real criminal network extracted from meetings emerging from the police physical surveillance during 2000s, we here aim to create artificial models that present similar properties. Methods: We use specific tools of s…
Descriptional and Computational Complexity of the Circuit Representation of Finite Automata
2018
In this paper we continue to investigate the complexity of the circuit representation of DFA—BC-complexity. We compare it with nondeterministic state complexity, obtain upper and lower bounds which differ only by a factor of 4 for a Binary input alphabet. Also we prove that many simple operations (determining if a state is reachable or if an automaton is minimal) are PSPACE-complete for DFA given in circuit representation.
The computational power of continuous time neural networks
1997
We investigate the computational power of continuous-time neural networks with Hopfield-type units. We prove that polynomial-size networks with saturated-linear response functions are at least as powerful as polynomially space-bounded Turing machines.
Some Afterthoughts on Hopfield Networks
1999
In the present paper we investigate four relatively independent issues, which complete our knowledge regarding the computational aspects of popular Hopfield nets. In Section 2 of the paper, the computational equivalence of convergent asymmetric and Hopfield nets is shown with respect to network size. In Section 3, the convergence time of Hopfield nets is analyzed in terms of bit representations. In Section 4, a polynomial time approximate algorithm for the minimum energy problem is shown. In Section 5, the Turing universality of analog Hopfield nets is studied. peerReviewed
Automata and forbidden words
1998
Abstract Let L ( M ) be the (factorial) language avoiding a given anti-factorial language M . We design an automaton accepting L ( M ) and built from the language M . The construction is effective if M is finite. If M is the set of minimal forbidden words of a single word ν, the automaton turns out to be the factor automaton of ν (the minimal automaton accepting the set of factors of ν). We also give an algorithm that builds the trie of M from the factor automaton of a single word. It yields a nontrivial upper bound on the number of minimal forbidden words of a word.
Heterogeneous network games: Conflicting preferences
2013
Proceeding at: 2nd Annual UECE Lisbon Meeting: Game Theory and Applications, took place 2010, November, 4-6, in Lisbon (Portugal). The event Web site http://pascal.iseg.utl.pt/~uece/lisbonmeetings2010/ In many economic situations, a player pursues coordination or anti-coordination with her neighbors on a network, but she also has intrinsic preferences among the available options. We here introduce a model which allows to analyze this issue by means of a simple framework in which players endowed with an idiosyncratic identity interact on a social network through strategic complements or substitutes. We classify the possible types of Nash equilibria under complete information, finding two thr…
Mean Field Linear Quadratic Games with Set Up Costs
2013
This paper studies linear quadratic games with set up costs monotonic on the number of active players, namely, players whose action is non-null. Such games arise naturally in joint replenishment inventory systems. Building upon a preliminary analysis of the properties of the best response strategies and Nash equilibria for the given game, the main contribution is the study of the same game under large population. We also analyze the influence of an additional disturbance in the spirit of the literature on H∞ control. Numerical illustrations are provided. © 2012 Springer Science+Business Media New York.
Comparative study of modelling the thermal efficiency of a novel straight through evacuated tube collector with MLR, SVR, BP and RBF methods
2021
Abstract Data-based methods are useful for accurate modelling of solar thermal systems. In this work, several artificial neural network (ANN) techniques are proposed to predict the thermal performance of an all-glass straight through evacuated tube solar collector. These are compared to support vector regression analysis. Extensive experimental data sets were collected for training the ANN models. Solar radiation intensity, ambient temperature, wind speed, mass flow rate and collector inlet temperature were selected as the input layer to predict the thermal efficiency of the solar collector. The prediction precision of the ANN models was compared to the multiple linear regression and suppor…