On the collective sort problem for distributed tuple spaces

In systems coordinated with a distributed set of tuple spaces, it is crucial to assist agents in retrieving the tuples they are interested in. This can be achieved by sorting techniques that group similar tuples together in the same tuple space, so that the position of a tuple can be inferred by similarity. Accordingly, we formulate the collective sort problem for distributed tuple spaces, where a set of agents is in charge of moving tuples up to a complete sort has been reached, namely, each of the N tuple spaces aggregate tuples belonging to one of the N kinds available. After pointing out the requirements for effectively tackling this problem, we propose a self-organizing solution resembling brood sorting performed by ants. This is based on simple agents that perform partial observations and accordingly take decisions on tuple movement. Convergence is addressed by a fully adaptive method for simulated annealing, based on noise tuples inserted and removed by agents on a need basis so as to avoid sub-optimal sorting. Emergence of sorting properties and scalability are evaluated through stochastic simulations.     

Experiments on the reliability of stochastic spiking neural P systems

In the area of membrane computing, time-freeness has been defined as the ability for a timed membrane system to produce always the same result, independently of the execution times associated to the rules. In this paper, we use a similar idea in the framework of spiking neural P systems, a model inspired by the structure and the functioning of neural cells. In particular, we introduce stochastic spiking neural P systems where the time of firing for an enabled spiking rule is probabilistically chosen and we investigate when, and how, these probabilities can influence the ability of the systems to simulate, in a reliable way, universal machines, such as register machines.     

A Model of Partially Observable State Game and its Optimality

In this paper we present a model of two-players partially observable state-game and study its optimality. The model is inspired by the practical problem of negotiation in a multi-agent system and formulates, from a the game theory point of view, the so-called contract net protocol. It covers a wide variety of real problems including some simple card games such as blackjack, and many negotiation and bargaining situations. The results that follow are valid for non-zero-sum games as well as for zero-sum games. Basically, we establish and prove the relation between partially observable state games and some classical (single-state) bi-matrix games. If the original state game is zero-sum, then the equivalent bi-matrix game is so.     

How “Authentic Intentionality” can be Enabled: a Neurocomputational Hypothesis

According to John Haugeland, the capacity for “authentic intentionality” depends on a commitment to constitutive standards of objectivity. One of the consequences of Haugeland’s view is that a neurocomputational explanation cannot be adequate to understand “authentic intentionality”. This paper gives grounds to resist such a consequence. It provides the beginning of an account of authentic intentionality in terms of neurocomputational enabling conditions. It argues that the standards, which constitute the domain of objects that can be represented, reflect the statistical structure of the environments where brain sensory systems evolved and develop. The objection that I equivocate on what Haugeland means by “commitment to standards” is rebutted by introducing the notion of “florid, self-conscious representing”. Were the hypothesis presented plausible, computational neuroscience would offer a promising framework for a better understanding of the conditions for meaningful representation.     

Deductive verification of alternating systems

Alternating systems are models of computer programs whose behavior is governed by the actions of multiple agents with, potentially, different goals. Examples include control systems, resource schedulers, security protocols, auctions and election mechanisms. Proving properties about such systems has emerged as an important new area of study in formal verification, with the development of logical frameworks such as the alternating temporal logic ATL*. Techniques for model checking ATL* over finite-state systems have been well studied, but many important systems are infinite-state and thus their verification requires, either explicitly or implicitly, some form of deductive reasoning. This paper presents a theoretical framework for the analysis of alternating infinite-state systems. It describes models of computation, of various degrees of generality, and alternating-time logics such as ATL* and its variations. It then develops a proof system that allows to prove arbitrary ATL* properties over these infinite-state models. The proof system is shown to be complete relative to validities in the weakest possible assertion language. The paper then derives auxiliary proof rules and verification diagrams techniques and applies them to security protocols, deriving a new formal proof of fairness of a multi-party contract signing protocol where the model of the protocol and of the properties contains both game-theoretic and infinite-state (parameterized) aspects.     

Gene regulatory networks reconstruction from time series datasets using genetic programming: a comparison between tree-based and graph-based approaches

Genetic programming researchers have shown a growing interest in the study of gene regulatory networks in the last few years. Our team has also contributed to the field, by defining two systems for the automatic reverse engineering of gene regulatory networks called GRNGen and GeNet. In this paper, we revise this work by describing in detail the two approaches and empirically comparing them. The results we report, and in particular the fact that GeNet can be used on large networks while GRNGen cannot, encourage us to pursue the study of GeNet in the future. We conclude the paper by discussing the main research directions that we are planning to investigate to improve GeNet.     

3D geometry reconstruction from orthographic views: A method based on 3D image processing and data fitting

Industrial esthetic designers typically produce hand-drawn sketches in the form of orthographic projections. A subsequent translation from 2D-drawings to 3D-models is usually necessary. This involves a considerably time consuming process, so that some automation is advisable.     

A proportional share allocation mechanism for coordination of plug-in electric vehiclecharging

The near-future penetration of plug-in electric vehicles is expected to be large enough to have a significant impact on the power grid. If PEVs were allowed to charge simultaneously at the maximum power rate, the distribution grid would face serious problems of stability. Therefore, mechanisms are needed to coordinate various PEVs that charge simultaneously. In this paper we propose an allocation mechanism that aims at balancing allocative efficiency and fairness, providing preferential treatment to the PEVs that have a high valuation of the available power, while guaranteeing a fair share of this power to all thePEVs.