1,721,111 research outputs found
Mechanism Design Approach for Energy Efficiency
No full textIn a real world, there exist different energy sources that provide the required energy (photovoltaic (PV), nuclear, hydroelectric, etc). Therefore, the trend of the amount of available energy is constantly changing by the day. At the other hand, the consumption of a community of users depends on users’ lifestyles, day of the week, season, ecc. In the literature, this kind of problem is called demand side management (DSM), that is the modification of consumer demand for energy through various methods such as financial incentives and behavioral change through education. During my research activities, I am developing a model that is able to manage the energy demand in order to reach an efficiency goal: consuming the whole produced energy. The model takes into account the social goal that is represented by the optimal use of the energy produced. This can be achieved by behavioural changes induced in the users modifying dynamically the energy cost per hour. In this work, I want to deploy a game-theoretic approach in order to tackle this DSM issue. The objective is to modify users’ behavior in order to avoid consumption peaks and to involve the users into a more careful energy consumption. The mechanism will be able to drive users in shifting energy consumptions, by selecting an appropriate energy pricing scheme considering the amount of available energy according to the energy consumption preference of every users. This result could be achieved through an incentive approach, for instance to give more expensive energy rate for specific peak hours. The aim is to develop a mechanism (in a game theoretic sense), that want to pursuit a global objective (the optimal energy use) through the independent maximization of single user’s utility, according to the definition of a social choice function and a payment scheme
A Nonmonotonic Soft Concurrent Constraint Language to Model the negotiation Process
No full textWe present an extension of the Soft Concurrent Constraint language that allows the nonmonotonic evolution of the constraint store. To accomplish this, we introduce some new operations: retract (c) reduces the current store by c, update(X) (c) transactionally relaxes all the constraints of the store that deal with the variables in the set X, and then adds a constraint c; nask (c) tests if c is not entailed by the store. The new retraction operators also permit to reason about Belief Revision, i.e. the process of changing beliefs to take into account a new piece of information. We present this framework as a possible solution to the negotiation of resources (e. g. web services and network resource allocation) that need a given Quality of Service (QoS). For this reason we also show the the new operators of the language satisfy the Belief Revision postulates [20], which can be used in the negotiation process. The QoS requirements (expressed as semiring levels) of all the parties should converge on a formal agreement through a negotiation process, which specifies the contract that must be enforced
A Secure Non-monotonic Soft Concurrent Constraint Language
No full textWe present a fine-grained security model to enforce the access control on the shared constraint store in Concurrent Constraint Programming (CCP) languages. We show the model for a non-monotonic version of Soft CCP (SCCP), that is an extension of CCP where the constraints have a preference level associated with them. Crisp constraints can be modeled in the same framework as well. In the considered non-monotonic soft version (NmSCCP), it is also possible to remove constraints from the store. The language can be used for coordinating agents on a common store of information that represents the set of shared resources. In such scenarios, it is clearly important to enforce the integrity and confidentiality rights on the resources, in order, for instance, to hide part of the information to some agents, or to prevent an agent to consume too many resources. Finally, we present a bisimulation relation to check equivalence between two programs written in this language
Solving Distributed CSPs Probabilistically
No full textConstraint solving problems (CSPs) are the formalization of a large range of problems that emerge fromcomputer science. The solving methodology described here is based on the naming game. The two main features that distinguish this methodology from most distributed constraint solving problem (DCSPs) methods are: the system can react to small instance changes, and it does not require pre-agreed agent/variable ordering. The naming game was introduced to represent N agents that have to bootstrap an agreement on a name to give to an object. The agents do not have a hierarchy, and use a minimal protocol. Still they converge to a consistent state by using a distributed strategy. For this reason, the naming game can be used to untangle DCSPs. It was shown that a distributed system of uniform finite state machines does not solve the ring ordering problem in all the algorithm executions. Our algorithm is a distributed uniform system of agents able to perform random decisions when presented with equivalent alternatives. We show that this algorithm solves the ring ordering problem with a probability one
Implementing and Testing a Formal Framework for Constraint-Based Routing over Scale-free Networks
No full textCoalitions of Arguments: An Approach with Constraint Programming
No full textThe aggregation of generic items into coalitions leads to the creation of sets of homogenous entities. In this paper we accomplish this for an input set of arguments, and the result is a partition according to distinct lines of thought, i.e., groups of "coherent" ideas. We extend Dung's Argumentation Framework (AF) in order to deal with coalitions of arguments. The initial set of arguments is partitioned into not-intersected subsets. All the found coalitions show the same property inherited by Dung, e.g., all the coalitions in the partition are admissible (or conflict-free, complete, stable): they are generated according to Dung's principles. Each of these coalitions can be assigned to a different agent. We use Soft Constraint Programming as a formal approach to model and solve such partitions in weighted AFs: semiring algebraic structures can be used to model different optimization criteria for the obtained coalitions. Moreover, we implement and solve the presented problem with JaCoP, a Java constraint solver, and we test the code over a small-world network
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