Set Of Possible Types Research Articles

Regret minimization in online Bayesian persuasion: Handling adversarial receiver's types under full and partial feedback models

In Bayesian persuasion, an informed sender has to design a signaling scheme that discloses the right amount of information so as to influence the behavior of a self-interested receiver. This kind of strategic interaction is ubiquitous in real-world economic scenarios. However, the seminal model by Kamenica and Gentzkow makes some stringent assumptions that limit its applicability in practice. One of the most limiting assumptions is, arguably, that the sender is required to know the receiver's utility function to compute an optimal signaling scheme. We relax this assumption through an online learning framework in which the sender repeatedly faces a receiver whose type is unknown and chosen adversarially at each round from a finite set of possible types. We are interested in no-regret algorithms prescribing a signaling scheme at each round of the repeated interaction with performances close to that of a best-in-hindsight signaling scheme. First, we prove a hardness result on the per-round running time required to achieve no-α-regret for any α<1. Then, we provide algorithms for the full and partial feedback models with regret bounds sublinear in the number of rounds and polynomial in the size of the instance. Finally, we show that, by relaxing the persuasiveness constraints on signaling schemes, it is possible to design an algorithm with a better running time and small regret.

On-line estimators for ad-hoc task execution: learning types and parameters of teammates for effective teamwork

It is essential for agents to work together with others to accomplish common objectives, without pre-programmed coordination rules or previous knowledge of the current teammates, a challenge known as ad-hoc teamwork. In these systems, an agent estimates the algorithm of others in an on-line manner in order to decide its own actions for effective teamwork. A common approach is to assume a set of possible types and parameters for teammates, reducing the problem into estimating parameters and calculating distributions over types. Meanwhile, agents often must coordinate in a decentralised fashion to complete tasks that are displaced in an environment (e.g., in foraging, de-mining, rescue or fire control), where each member autonomously chooses which task to perform. By harnessing this knowledge, better estimation techniques can be developed. Hence, we present On-line Estimators for Ad-hoc Task Execution (OEATE), a novel algorithm for teammates’ type and parameter estimation in decentralised task execution. We show theoretically that our algorithm can converge to perfect estimations, under some assumptions, as the number of tasks increases. Additionally, we run experiments for a diverse configuration set in the level-based foraging domain over full and partial observability, and in a “capture the prey” game. We obtain a lower error in parameter and type estimation than previous approaches and better performance in the number of completed tasks for some cases. In fact, we evaluate a variety of scenarios via the increasing number of agents, scenario sizes, number of items, and number of types, showing that we can overcome previous works in most cases considering the estimation process, besides robustness to an increasing number of types and even to an erroneous set of potential types.

Ligand-Linked Association-Dissociation in Transport Proteins and Hormone Receptors.

Ligand-linked changes in the aggregation state of biological macromolecules occur and have importance in several physiological processes, e.g., the response of hormone receptors, cooperative ligand binding, and others. The mathematical formalisms that express the thermodynamics governing these processes are complex, as they are required to describe observations made under experimental conditions in which many parameters may be simultaneously varied. The description of the functional behaviour of proteins that present ligand-linked association-dissociation events must accommodate cases where both the binding stoichiometries and reaction mechanisms are variable. In this paper, we review some paradigmatic cases that cover different structural arrangements and binding modes, with special attention to the case of dissociating homodimeric transport proteins and receptors. Even though we cannot pretend to be comprehensive on the proteins presenting this behaviour, we believe that we can attempt to be comprehensive on the structural arrangements and thermodynamic properties of these systems, which fall into a limited set of possible types.

Heartbeat monitoring from adaptively down-sampled electrocardiogram

Background and ObjectiveHeartbeats Holter monitoring is important for the detection of arrhythmias and possible anomalies, which are predictive of cardiovascular risks and infections. Reducing the number of acquired samples is useful to save energy and memory, but a proper down-sampling schedule is needed to record all useful information. MethodAn adaptive algorithm for the non-uniform down-sampling of data is used to reduce the mean sampling frequency of ECG data. The acquired data are processed to extract RR rhythm and to classify the heartbeats among a set of possible types of arrhythmias. ResultsThe proposed method is tested in terms of the ability to estimate the heart rate and to classify the heartbeats from the MIT-BIH Arrhythmia data down-sampled below the Nyquist limit. The mean accuracy in identifying the heartbeats was over the 98% and the RMS error in estimating the RR time series was lower than the 1%. Variability, spectral and complexity indexes extracted from RR series were estimated with a mean error that was lower than 10%. Classification accuracy was above the 95%. ConclusionsAn adaptive method to down-sample ECG data is discussed. It can be useful to save energy and to reduce memory occupation, while still preserving important information on the heartbeats.

Regression analysis of competing risks data with general missing pattern in failure types

In competing risks data, missing failure types (causes) is a very common phenomenon. In a general missing pattern, if a failure type is not observed, one observes a set of possible types containing the true type along with the failure time. Dewanji and Sengupta (2003) considered nonparametric estimation of the cause-specific hazard rates and suggested a Nelson–Aalen type estimator under such general missing pattern. In this work, we deal with the regression problem, in which the cause-specific hazard rates may depend on some covariates, and consider estimation of the regression coefficients and the cause-specific baseline hazards under the general missing pattern using some semi-parametric models. We consider two different proportional hazards type semi-parametric models for our analysis. Simulation studies from both the models are carried out to investigate the finite sample properties of the estimators. We also consider an example from an animal experiment to illustrate our methodology.

A novel computational approach “BP-STOCH” to study ligand binding to finite lattice

We report a novel computational algorithm "BP-STOCH" to be used for studying single-type ligand binding with biopolymers of finite lengths, such as DNA oligonucleotides or oligopeptides. It is based on an idea to represent any type of ligand-biopolymer complex in a form of binary number, where "0" and "1" bits stand for vacant and engaged monomers of the biopolymer, respectively. Cycling over all binary numbers from the lowest 0 up to the highest 2(N) - 1 means a sequential generating of all possible configurations of vacant/engaged monomers, which, after proper filtering, results in a full set of possible types of complexes in solution between the ligand and the N-site lattice. The principal advantage of BP-STOCH algorithm is the possibility to incorporate into this cycle any conditions on computation of the concentrations and observed experimental parameters of the complexes in solution, and programmatic access to each monomer of the biopolymer within each binding site of every binding configuration. The latter is equivalent to unlimited extension of the basic reaction scheme and allows to use BP-STOCH algorithm as an alternative to conventional computational approaches.

A parameter-adaptive dynamic programming approach for inferring cophylogenies

BackgroundCoevolutionary systems like hosts and their parasites are commonly used model systems for evolutionary studies. Inferring the coevolutionary history based on given phylogenies of both groups is often done by employing a set of possible types of events that happened during coevolution. Costs are assigned to the different types of events and a reconstruction of the common history with a minimal sum of event costs is sought.ResultsThis paper introduces a new algorithm and a corresponding tool called CoRe-PA, that can be used to infer the common history of coevolutionary systems. The proposed method utilizes an event-based concept for reconciliation analyses where the possible events are cospeciations, sortings, duplications, and (host) switches. All known event-based approaches so far assign costs to each type of cophylogenetic events in order to find a cost-minimal reconstruction. CoRe-PA uses a new parameter-adaptive approach, i.e., no costs have to be assigned to the coevolutionary events in advance. Several biological coevolutionary systems that have already been studied intensely in literature are used to show the performance of CoRe-PA.ConclusionFrom a biological point of view reasonable cost values for event-based reconciliations can often be estimated only very roughly. CoRe-PA is very useful when it is difficult or impossible to assign exact cost values to different types of coevolutionary events in advance.

Nonparametric estimation of bivariate survivor function under masked causes of failure

Consider a system that consists of k components. Each component is subject to more than one cause of failure. Due to inadequacy in the diagnostic mechanism or reluctance to report any specific cause of failure (disease), the exact cause of failure cannot be identified easily. In such situations, where the cause of failure is masked, test procedures restrict the cause of failure to a set of possible types containing the true failure cause. In this paper, we develop a nonparametric estimator for the bivariate survivor function of competing risk models under masked causes of failure based on the vector hazard rate. Asymptotic properties of the estimator are established. A simulation study is carried out to assess the performance of the estimator. We also illustrate the method with a data set.

Selfish Routing with Incomplete Information

In his seminal work, Harsanyi (Manag. Sci. 14, 159–182, 320–332, 468–502, 1967) introduced an elegant approach to study non-cooperative games with incomplete information. In our work, we use this approach to define a new selfish routing game with incomplete information that we call Bayesian routing game. Here, each of n selfish users wishes to assign its traffic to one of m parallel links. However, users do not know each other’s traffic. Following Harsanyi’s approach, we introduce, for each user, a set of possible types. In our model, each type of a user corresponds to some traffic and the players’ uncertainty about each other’s traffic is described by a probability distribution over all possible type profiles. We present a comprehensive collection of results about our Bayesian routing game. Our main findings are as follows: Using a potential function, we prove that every Bayesian routing game has a pure Bayesian Nash equilibrium. More precisely, we show this existence for a more general class of games that we call weighted Bayesian congestion games. For Bayesian routing games with identical links and independent type distribution, we give a polynomial time algorithm to compute a pure Bayesian Nash equilibrium. We study structural properties of fully mixed Bayesian Nash equilibria for the case of identical links and show that they maximize Individual Cost. In general, there is more than one fully mixed Bayesian Nash equilibrium. We characterize fully mixed Bayesian Nash equilibria for the case of independent type distribution. We conclude with bounds on Coordination Ratio for the case of identical links and for three different Social Cost measures: Expected Maximum Latency, Sum of Individual Costs and Maximum Individual Cost. For the latter two, we are able to give (asymptotically) tight bounds using the properties of fully mixed Bayesian Nash equilibria we proved.

Estimation of competing risks with general missing pattern in failure types.

In competing risks data, missing failure types (causes) is a very common phenomenon. In this work, we consider a general missing pattern in which, if a failure type is not observed, one observes a set of possible types containing the true type, along with the failure time. We first consider maximum likelihood estimation with missing-at-random assumption via the expectation maximization (EM) algorithm. We then propose a Nelson-Aalen type estimator for situations when certain information on the conditional probability of the true type given a set of possible failure types is available from the experimentalists. This is based on a least-squares type method using the relationships between hazards for different types and hazards for different combinations of missing types. We conduct a simulation study to investigate the performance of this method, which indicates that bias may be small, even for high proportion of missing data, for sufficiently large number of observations. The estimates are somewhat sensitive to misspecification of the conditional probabilities of the true types when the missing proportion is high. We also consider an example from an animal experiment to illustrate our methodology.

Propagation of a short pulse in a medium with a resonance relaxation: The exact solution

A new analytical representation is obtained for the fundamental solution (Green’s function) to the problem of the propagation of a short pulse in an arbitrary medium with a single resonance relaxation process. The analytical representation is based on the generalized function of the local response of a linear medium [1] and includes the well-known Debye and Lorentz relaxation models as particular cases. The representation is used to determine the complete set of possible types of behavior for a short pulse propagating in the medium.

Abstract types defined as classes of variables

The concept of “type” has been used without a precise definition in discussions about programming languages for 20 years. Before the concept of user defined data types was introduced, a definition was not necessary for discussions of specific programming languages. The meaning of the term was implicit in the small list of possible types supported by the language. There was even enough similarity between different languages so that this form of definition allowed discussions of languages in general. The need for a widely accepted definition of type became clear in discussions of languages that allow users to add to the set of possible types without altering the compiler. In such languages, the concept of type is no longer implicitly defined by the set of built-in types. A consistent language must be based on a clearer definition of the notion of type than we now have.

Abstract types defined as classes of variables

The concept of “type” has been used without a precise definition in discussions about programming languages for 20 years. Before the concept of user defined data types was introduced, a definition was not necessary for discussions of specific programming languages. The meaning of the term was implicit in the small list of possible types supported by the language. There was even enough similarity between different languages so that this form of definition allowed discussions of languages in general. The need for a widely accepted definition of type became clear in discussions of languages that allow users to add to the set of possible types without altering the compiler. In such languages, the concept of type is no longer implicitly defined by the set of built-in types. A consistent language must be based on a clearer definition of the notion of type than we now have.