Technologies of Conflict

We explore theoretical foundations and issues in the empirical estimation of conflict technologies. Such technologies are probabilistic choice functions that depend on the military capacities of adversaries, where the military capacities themselves depend on economic inputs via ordinary production functions. Different classes of functional forms can be derived stochastically or axiomatically. The additive form, in particular, (which includes both the logit and ratio functional forms) has both stochastic and axiomatic foundations. Issues in the empirical estimation that we explore include concerns with data, endogeneity, structural breaks, and model comparison.

Fuzzy and probabilistic choice functions : a new set of rationality conditions

Probabilistic and fuzzy choice theory are used to describe decision situations in which a certain degree of imprecision is involved. In this work we propose a correspondence between probabilistic and fuzzy choice functions, based on implication operators. Given a probabilistic choice function a fuzzy choice function can be constructed and, furthermore, a new set of rationality conditions is proposed. Finally, we prove that under those conditions, the associated fuzzy choice function fulfills desirable rationality properties

Fuzzy and probabilistic choice functions: a new set of rationality conditions

IFSA-EUSFLAT'2015: 16th World Congress of the International Fuzzy Systems Association and 9th Conference of the European Society for Fuzzy Logic and Technlogy, July 2015, Gijón, SpainProbabilistic and fuzzy choice theory are used to describe decision situations in which a certain degree of imprecision is involved. In this work we propose a correspondence between probabilistic and fuzzy choice functions, based on implication operators. Given a probabilistic choice function a fuzzy choice function can be constructed and, furthermore, a new set of rationality conditions is proposed. Finally, we prove that under those conditions, the associated fuzzy choice function fulfills desirable rationality propertie

Bridging probabilistic and fuzzy approaches to choice under uncertainty

Imprecise choices can be described using either a probabilistic or a fuzzy formalism. No relation between them has been studied so far. In this contribution we present a connection between the two formalisms that strongly makes use of fuzzy implication operators and t-norms. In this framework, Luce's Choice Axiom turns out to be a special case when the product t-norm is considered and other similar choice axioms can be stated, according to the t-norm in use. Also a new family of operators for transforming bipolar relations into unipolar ones is presented

A Parameterisation of Algorithms for Distributed Constraint Optimisation via Potential Games

This paper introduces a parameterisation of learning algorithms for distributed constraint optimisation problems (DCOPs). This parameterisation encompasses many algorithms developed in both the computer science and game theory literatures. It is built on our insight that when formulated as noncooperative games, DCOPs form a subset of the class of potential games. This result allows us to prove convergence properties of algorithms developed in the computer science literature using game theoretic methods. Furthermore, our parameterisation can assist system designers by making the pros and cons of, and the synergies between, the various DCOP algorithm components clear

Persuasion as a Contest

From marketing and advertising to political campaigning and court proceedings, contending parties expend resources to persuade an audience of the correctness of their view. We examine how the probability of persuading the audience depends on the resources expended by the parties, so that persuasion can be modelled as a contest. We use a Bayesian approach whereby the audience makes inferences solely based on the evidence presented to them. The evidence is produced by the resources expended by the contending parties. We find conditions on evidence production and likelihood functions that yield the well-known additive contest success functions, including the logit function as well as the one used in all-pay auctions. We also find conditions that produce a "difference" functional form. In all cases, there are three main determinants of which side the audience chooses: (i) the truth and other objective parameters of the environment; (ii) the biases of the audience as distilled in their priors and the likelihood function employed; and (iii) the resources expended by the parties interested in persuading the audience.Rent-seeking; Advertising; Litigation; Political campaigning; Property rights

Persuasion as a Contest

From marketing and advertising to political campaigning and court proceedings, contending parties expend resources to persuade an audience of the correctness of their view. We examine how the probability of persuading the audience depends on the resources expended by the parties, so that persuasion can be modelled as a contest. We use a Bayesian approach whereby the audience makes inferences solely based on the evidence presented to them. The evidence is produced by the resources expended by the contending parties. We find conditions on evidence production and likelihood functions that yield the well-known additive contest success functions, including the logit function as well as the one used in all-pay auctions. We also find conditions that produce a “difference” functional form. In all cases, there are three main determinants of which side the audience chooses: (i) the truth and other objective parameters of the environment; (ii) the biases of the audience as distilled in their priors and the likelihood function employed ; and (iii) the resources expended by the parties interested in persuading the audience.rent-seeking, advertising, litigation, political campaigning, property rights

The Logit Equilibrium: A Perspective on Intuitive Behavioral Anomalies

This paper considers a class of models in which rank-based payoffs are sensitive to small amounts of noise in decision making. Examples include auction, price-competition, coordination, and location games. Observed laboratory behavior in these games is often responsive to asymmetric costs associated with deviations from the Nash equilibrium. These payoff asymmetry effects are incorporated in an approach that introduces noisy behavior via probabilistic choice. In equilibrium, behavior is characterized by a probability distribution that satisfies a "rational expectations" consistency condition: the beliefs that determine player's expected payoffs match the decision distributions that arise from applying a logit probabilistic choice function to those expected payoffs. We prove existence of a unique, symmetric logit (quantal response) equilibrium and derive comparative statics results. The paper provides a unified perspective on many recent laboratory studies of games in which Nash equilibrium predictions are inconsistent with both intuition and experimental evidence.logit equilibrium, quantal response equilibrium, probabilistic choice, auctions.

Transportation Systems with Autonomous Vehicles: Models and algorithms for equilibrium assignment

Abstract Technologies for connected, automated or autonomous vehicles (AVs) are fast developing, so that they seem ready for substituting in the near future privately owned non-autonomous traditional vehicles (TVs) and further supporting the spread of shared vehicles both for person and good transportation. On the other hand, it may easily be anticipated that the time needed to turn the existing stock of TVs into AVs will last several years during which mixed traffic is expected. A change so great may be not technology-driven only, but also requires a carefully analysis of its several impact through well designed enhancements of tools already available to the transportation systems modelers and planners. Such enhanced tools may be casted in the general framework of multi-user class assignment to transportation networks, concerning: (i) transportation network analysis, through level-of-service models distinguishing between non-autonomous vs. autonomous vehicles, presumably sharing same infrastructure; (ii) travel demand analysis, through behavioral choice modeling paradigms, including choice between AVs vs. TVs, owned vs. shared, as well as route choice behavior; (iii) steady-state equilibrium assignment. This paper describes models and algorithms to deal with steady-state equilibrium assignment; they are used to show to which extent existing methods can still be applied as well as which issues remain still open and worth of further research efforts

Cooperative agent-based software architecture for distributed simulation

This paper proposes a cooperative multiagent model using distributed object-based systems for supporting distributed virtual environment and distributed simulation technologies for military and government applications. The agent model will use the condition-event driven rule based system as the basis for representing knowledge. In this model, the updates and revision of beliefs of agents corresponds to modifying the knowledge base. These agents are reactive and respond to stimulus as well as the environment in which they are embedded. Further, these agents are smart and can learn from their actions. The distributed agent-based software architecture will enable us to realise human behaviour model environment and computer-generated forces (also called computer-generated actor (CGA)) architectures. The design of the cooperative agent-based architecture will be based on mobile agents, interactive distributed computing models, and advanced logical modes of programming. This cooperative architecture will be developed using Java based tools and distributed databases