Strongly Essential Coalitions and the Nucleolus of Peer Group Games

Most of the known efficient algorithms designed to compute the nucleolus for special classes of balanced games are based on two facts: (i) in any balanced game, the coalitions which actually determine the nucleolus are essential; and (ii) all essential coalitions in any of the games in the class belong to a prespeci ed collection of size polynomial in the number of players.We consider a subclass of essential coalitions, called strongly essential coalitions, and show that in any game, the collection of strongly essential coalitions contains all the coalitions which actually determine the core, and in case the core is not empty, the nucleolus and the kernelcore.As an application, we consider peer group games, and show that they admit at most 2n - 1 strongly essential coalitions, whereas the number of essential coalitions could be as much as 2n-1. We propose an algorithm that computes the nucleolus of an n-player peer group game in O(n2) time directly from the data of the underlying peer group situation.game theory;algorithm;cooperative games;kernel estimation;peer games

Model checking coalitional games in shortage resource scenarios

Verification of multi-agents systems (MAS) has been recently studied taking into account the need of expressing resource bounds. Several logics for specifying properties of MAS have been presented in quite a variety of scenarios with bounded resources. In this paper, we study a different formalism, called Priced Resource-Bounded Alternating-time Temporal Logic (PRBATL), whose main novelty consists in moving the notion of resources from a syntactic level (part of the formula) to a semantic one (part of the model). This allows us to track the evolution of the resource availability along the computations and provides us with a formalisms capable to model a number of real-world scenarios. Two relevant aspects are the notion of global availability of the resources on the market, that are shared by the agents, and the notion of price of resources, depending on their availability. In a previous work of ours, an initial step towards this new formalism was introduced, along with an EXPTIME algorithm for the model checking problem. In this paper we better analyze the features of the proposed formalism, also in comparison with previous approaches. The main technical contribution is the proof of the EXPTIME-hardness of the the model checking problem for PRBATL, based on a reduction from the acceptance problem for Linearly-Bounded Alternating Turing Machines. In particular, since the problem has multiple parameters, we show two fixed-parameter reductions.Comment: In Proceedings GandALF 2013, arXiv:1307.416

Contributions to distributed MPC: coalitional and learning approaches

A growing number of works and applications are consolidating the research area of distributed control with partial and varying communication topologies. In this context, many of the works included in this thesis focus on the so-called coalitional MPC. This approach is characterized by the dynamic formation of groups of cooperative MPC agents (referred to as coalitions) and seeks to provide a performance close to the centralized one with lighter computations and communication demands. The thesis includes a literature review of existing distributed control methods that boost scalability and flexibility by exploiting the degree of interaction between local controllers. Likewise, we present a hierarchical coalitional MPC for traffic freeways and new methods to address the agents' clustering problem, which, given its combinatoria! nature, becomes a key issue for the real-time implementation of this type of controller. Additionally, new theoretical results to provide this clustering strategy with robust and stability guarantees to track changing targets are included. Further works of this thesis focus on the application of learning techniques in distributed and decentralized MPC schemes, thus paving the way for a future extension to the coalitional framework. In this regard, we have focused on the use of neural networks to aid distributed negotiations, and on the development of a multi­ agent learning MPC based on a collaborative data collection

A Comparative Analysis of Indigenous Displacement and the World War II Japanese American Internment

Article in special issue of Amerasia Journal on "Carceral States

Estimating social relation from trajectories

This study focuses on social pedestrian groups in public spaces and makes an effort to identify the social relation between the group members. We particularly consider dyads having coalitional or mating relation. We derive several observables from individual and group trajectories, which are suggested to be distinctive for these two sorts of relations and propose a recognition algorithm taking these observables as features and yielding an estimation of social relation in a probabilistic manner at every sampling step. On the average, we detect coalitional relation with 87% and mating relation with 81% accuracy. To the best of our knowledge, this is the first study to infer social relation from joint (loco)motion patterns and we consider the detection rates to be a satisfactory considering the inherent challenge of the problem

Cooperative Game Theory and Its Application in Localization Algorithms

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